Having spent many years in a long distance relationship, I learned firsthand how hard it is to keep one flirty, fun, and fiesty. Luckily, text messages can be your ally. Are you tired of telling your partner what you made for dinner? Or sending the same "I miss you" text? Read on for some fresh ideas on how to keep your connection strong over any distance.
Being apart is never easy. However, there are definitely some positive aspects to living in different places. Are you scratching your head trying to think of something good? How about the fact that everything around you is somewhat foreign to your partner? Think of yourself as their "eyes." You choose what to share with them and what other bits you'd like to leave aside.
Now, take a deep breath, put on your thinking cap, and lock your cell phone before you start bombarding your partner with mile long texts whining about your co-workers or the long lines at the poorly stocked supermarket. Use long distance texting to your advantage by taking a minute to decide what you hope to gain from your text mission.
– Do you want your partner to eventually pack up their bags and move to wherever you are?
– Are you clear on the amount of time you will be apart? Are your texts simply a means to keep your relationship healthy during your separation?
– Or, are you confident about your relationship, or are you anxious to discover if you and your partner are really meant to be together?
There is no right or wrong answer. Everything depends on you, your partner, and your particular situation. The only thing that you should try to avoid is aimless texting. While venting and complaining may seem like interesting texting material to you, it will soon sap the fun and romance right out of your relationship.
Have fun with long distance texting and use the time apart to your advantage…make them crave more than your messages, make them crave you!
I always text her butvher response is not welcoming.what can i do to keep it alive?


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AIA CEO Robert Ivy To Receive Lifetime Achievement Award
Executive Vice President and Chief Executive Officer of the American Institute of Architects, Robert Ivy, was awarded the Noel Polk Lifetime Achievement Award by the Mississippi Institute of Arts and Letters.
The Polk Award, given to individuals with ties to the Mississippi area for notable and exceptional careers in the arts, has been awarded to luminaries such as Pulitzer Prize winning novelist Eudora Welty in 2001, late historian Shelby Foote in 2004 and Academy Award winning actor Morgan Freeman in 2007. Ivy will be the first architect ever to receive the award.
President of the MIAL Nancy LaForge in a statement praised Ivy for "making architecture more accessible to the general public", while President of AIA Carl Elefante congratulated Ivy, calling him a "worthy ambassador for our profession" and describing the honor as a "crowning personal and professional achievement for him as a native of Mississippi".
Follow Robert Ivy on LinkedIn
Robert Ivy is the holder of a Bachelor of Arts in English from Sewanee: The University of the South, as well as a Masters of Architecture from Tulane University. He launched an editorial career in 1996 as Editor in Chief of Architectural Record before becoming Vice President and Executive Director at the construction media arm of McGraw-Hill Education.
Named CEO of the AIA in 2011, Ivy has made it a priority to transform the institute into a technologically forward-thinking organization, while also increasing its public awareness to the benefit of its more than 90,000 members – the highest level of membership in the institute's 160-year history.
The American Institute of Architects was founded in 1857 by a group of thirteen New York architects, with the intent of forming an organization dedicated to the promotion of architecture in the public sphere. Today, the institute is headquartered in Washington, D.C., while also boasting 260 chapters and over 90,000 members across the globe and continuing to undertake public health and government advocacy in pursuance of its founding objective.
Learn more about Robert Ivy: http://www.architectmagazine.com/awards/robert-ivy-receives-noel-polk-lifetime-achievement-award_o

redpajama_set_name: RedPajamaCommonCrawl


2010 Halloween Show Details Right Here!
We're heading to Six Flags for Fright Fest when the whole park goes nuts for Halloween! Have a look below at some pics from our show there last year. You can get reduced price tix here. Enter this when prompted: USER NAME: livega (Case Sensitive) PASSWORD: SixFlags1 Here are some pics from the from last year's show.


This day I may be exposed to great peril, let me have the serpent's wisdom to keep out of it and avoid it. The wings of a dove may be of more use to me today than the jaws of a lion. It is true I may be an apparent loser by declining evil company, but I had better leave my cloak than lose my character; it is not needful that I should be rich, but it is imperative upon me to be pure. No ties of friendship, no chains of beauty, no flashings of talent, no shafts of ridicule must turn me from the wise resolve to flee from sin. The devil I am to resist and he will flee from me, but the lusts of the flesh, I must flee, or they will surely overcome me. O God of holiness preserve thy Josephs, that Madam Bubble bewitch them not with her vile suggestions. May the horrible trinity of the world, the flesh, and the devil, never overcome us!


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Dawie Roodt
Unemployment and poverty will increase yet again
Like it or not, Suleimani was an Iranian state actor
Better for world and life on Earth for Russia to be in charge
Fabian Fjälling
Sweden's democracy is decaying. Reporters are prevented by police to do their job, academics are arrested.
The dirtiest means to finish or destroy anti-immigrationists
Mayor Hidalgo; Festival; White protester
Mayor of Paris gives segregated black festival a thumbs up
The mayor of Paris, Anne Hidalgo, announced in a series of tweets that a "clear solution was established" regarding the organisation of the Afro-feminist festival Nyansapo, banning whites from participating: It would continue banning whites.
Published: May 31, 2017, 9:24 am
'Clear as all hell' why migrants burn Sweden
'White trash' and left-wing snobbery
'No blacks' says French rental agency
'Europe will need 6 million immigrants'
'Europe of free nations can be more unified than Europe under the dictates of Brussels'
This week Hiladgo declared apartheid, saying that that the all-black workshops would go ahead anyway: "The festival organised in a public place will be open to all. Non-mixed workshops will be held elsewhere, in a strictly private setting."
The mayor has called for a black feminist festival to be banned earlier because she said it was prohibited to white people.
A "compromise" was found in segregation after the "firm intervention yesterday [Sunday] with the organisers". But the Mwasi collective explained soon after that the segregation had in fact been planned since the beginning.
The Mwasi collective, which organised the afro-feminist event, was caustic in their response: "So, basically, our original program has absolutely not changed. We are now awaiting a formal communiqué from the Paris City Council, and a public apology," the members of the association told Twitter.
Hidalgo on Sunday had called for the Nyansapo Festival in the French capital to be postponed, which is due to run from July 28 to 30 at a government sponsored cultural centre.
The event was promoted as "rooted in black feminism, activism, and on a European scale", and 80 percent of the festival area will be set aside as a segregated "non-mixed" space "for black women only" according to its French website.
The English version of the site does not use the word "non-mixed" but translated the racial apartheid with "reserved".
Hidalgo, a Socialist, had said on Twitter that she "firmly condemned" the organisation "of this event, prohibited to white people" and added that she reserved the right "to prosecute the organisers for discrimination". It turned out to be a completely empty threat.
Police prefect Michel Delpuech said in a statement that police had not been advised about the event by Sunday evening.
SOS Racisme described the event as "a mistake, even an abomination, because it wallows in ethnic separation, whereas anti-racism is a movement which seeks to go beyond race".
The Mwasi collective was founded in 2014 by a group of African women and mixed race people who felt the need to express their views related to "oppressions" related to class, gender, sexuality or religion.
Of the four distinct spaces, three are reserved for black women, black people, and "racialised" women.
Not only SOS Racisme and the Licra were indignant at the separatist principles, but also the Front National had questioned the mayor of Paris about this "festival forbidden to whites".
The Afro-feminist collective Mwasi denounced the complaints as "a campaign of disinformation and fake news orchestrated by the most outdated extreme right".
They added: "We are saddened to see some anti-racist associations let themselves be manipulated. They find themselves paradoxically on the side of racists to stigmatize those who pragmatically advocate for the values of equality and respect." The collective published the added text on Sunday on its site.
It is not the first time that such apartheid and segregation made the news in France. In 2016, the organisation of a "decolonial summer camp" in Reims had promoted a "training seminar on anti-racism", reserved for victims of what they called "state racism", excluding white people.
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gearbox123
So we can have whites-only spaces, then?
Just kidding, I assume that would still be RAAAAAAAAAAAAAAAACIST.
Hi, I'm just been thawed after cryogenic freezing for 70 years. Why are blacks in France?
They're two countries, plus Gibraltar, away from Africa you dumb nazi cuck.
And the French surrendered…
Nigerians terrorize Italian city
PaduaThe Nigerian mafia has been busy in the Italian city of Padua. In less than 24 hours there were two violent episodes in the city center, and as always on via Diego Valeri.
France: 41 percent 'ignore' news
A survey carried out for a newspaper shows a growing distrust of the French towards the media.
Gang rapes: Number of foreign suspects in Germany increasing
BerlinThe proportion of foreign suspects in gang rapes in Germany has increased significantly in the past five years. This is despite the fact that the total number of suspects decreased between 2015 and 2017.
Candidate recruits people of 'Turkish origin' for French municipal elections
Given the extent of the controversy, Mohamed Dine has now deleted his ad, previously posted on his Facebook page.
Charlie Hebdo also defended pedophilia
ParisLike part of the libertarian left at the time, the satirical newspaper supported three pedophile criminals, accused of having abused minors, before they were sentenced in 1977.
Conservative German author's reading cancelled in Dresden
DresdenGerman author Uwe Tellkamp had his reading cancelled. It was not because of a lack of public interest, illness of the organiser or an important participant, or official orders for violations of the fire protection regulations. No, it had to be canceled because the author has a certain opinion.
Pedophile personalities shake up French literary scene
ParisThe French writer Gabriel Matzneff who has been accused by the novelist Vanessa Springora of pedophilia, benefits from low-cost housing in the heart of Paris which was allocated to him in 1994. Some other sordid facts about him and his friends have resurfaced.
AfD sues German domestic spy agency over tracking
BerlinThe AfD intends to take legal action against the Federal Office for the Protection of the Constitution, the domestic spy agency.
Dispute over German broadcaster's "environmental pig" song continues
CologneSeveral editors from German public broadcaster WDR have accused director Tom Buhrow of harming the broadcaster with the so-called "environmental pig" affair. On Tuesday there will therefore be an editorial meeting in which Buhrow will also take part.
Cars in flames all over France at the start of the New Year
The car-burnings in France continue. There were burnt cars in Strasbourg, Bordeaux, Limoges, Nantes and other cities.
Some 150 neighbourhoods 'held' by Islamists says French classified report
Belgium: Former ISIS recruiter attending school with youngsters
New grooming gang abuse scandal hits UK
'Feminized' signs installed at Geneva's pedestrian crossings
Spain's minister pleads for 'millions and millions' of immigrants
German expert report: No evidence of Russian troops in Donbass
EU's political disputes set to increase says Hungarian official
Marine Le Pen announces her candidacy for 2022
Finland: Human trafficking at record high
Thunberg's messages are written by her father bug reveals
Is Brussels preparing to 'poison' rice?
Matzneff affair in France exposes opportunism of leftists
Antifa extremists injure students in Vienna
Siemens offers Thunberg-sidekick a seat on supervisory board
More New Year's violence in Netherlands but fewer people arrested
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OC Overland was founded in April, 2017 with only one thought in mind, connecting the community and giving back as much as possible.
What started out as a group of 3 great friends turned into something bigger than we had ever hoped to imagine.
We remember back when we started the forums were the #1 source to find information about mods, trail runs and finding new people to ride with. We were looking for a more personal way to connecting with people from our community, to be more hands on and direct.
Who do you call to romp a day run? Who could I ask for mod advice? How could we get people to go camping? Where can I get trail info?
We didn't know either, this is how OCO became. It was then set and our goal was to be the source for all these questions and connecting one person to the next. Bringing different people together from different cities all over.
Inbox's begin to fill, comments began to trickle in, people were reaching out.
Our beliefs? GRASS ROOTS. Elevating people, bringing people together and giving people a family to join. We don't believe in making a dollar off of people who want to be a part of something; we welcome everyone to join our family with open arms regardless of your background, what you drive, or what you have been through. Which is a major reason why our events draw 30,40,50 rigs at a time on dirt or 500+ (1 year event at Cabe Toyota). Our patches and decals, we produce are 100% FREE, all we ask is you come out and join us and feel the camaraderie, the family atmosphere that our crew exudes. The one's listed on the site are for donation purposes and you can still get your free schwag by attending one of our trips.
The all for one and one for all attitude that we preach.
The love and support our community has shown us is humbling, and this is why we will not stop giving back and continue to use our platform to help others.
We hope to see ya'll at one of our events soon!


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Omicron found in U.S. + What to know about new sex abuse lawsuit against UNCSA
Kristen Kornbluth
Hi, Charlotteans! This is Kristen. Today at the Observer, we're honoring the iconic composer and lyricist of Broadway musicals, Stephen Sondheim, after his November death. Here are 10 ways arts editor Adam Bell remembers the man and his music. Rest in peace, Stephen.
Now for today's news:
1. California confirms first US case of omicron COVID-19 variant
The first U.S. case of the omicron COVID-19 variant was found in California. According to the U.S. Centers for Disease Control and Prevention, public health officials in California and San Francisco confirmed it.
Who had the case? A fully vaccinated traveler who returned from South Africa on Nov. 22.
Where was it found? Officials did not confirm the city or region.
How is the person doing? They have mild symptoms that are improving, a CDC release said.
The U.S. restricted travel from South Africa and eight other nations on Monday as details about the variant emerged. Not much is known about omicron yet, but officials urge people to continue taking preventative measures, like wearing masks, washing hands and practicing social distancing, and getting vaccinated.
2. What to know about new sex abuse lawsuit against UNC School of the Arts
The University of North Carolina School of the Arts in Winston-Salem, N.C., pictured here on July 19, 2021, is a creative and performing arts conservatory for high school and college students.
Months after North Carolina's arts university faced new claims that it mishandled sex abuse in the 1980s, dozens of alumni have contributed to a lawsuit calling for accountability.
A new complaint was filed Monday. Nearly 40 former students say they were sexually abused while enrolled at the University of North Carolina School of the Arts.
With the Observer's Sara Coello, find out what the new filing reveals, who's involved and what's next.
3. Today's business news
About 2,000 employees will be hired to work at Lowe's tech center hub office at Design Center Tower at 100 W. Worthington Ave. in South End.
$318 million sale of Lowe's office tower in South End sets a record in Charlotte by Gordon Rago
At 357,526 square feet, the tower at 100 W. Worthington Ave. went for $889 per square foot, county property records show.
Moving Honeywell to Charlotte is 'one of the best decisions we've ever made,' CEO says by Hannah Lang
Electronics manufacturer Honeywell celebrated the grand opening of its uptown headquarters Wednesday.
4. Unpacking 'moonshot' CMS goals after a lackluster year in student test scores
This fall, only 4.5% of CMS high school students scored high enough on exams to be considered performing at the college or career level in math skills compared to the statewide average of 6.5%.
To combat this, Charlotte-Mecklenburg Schools' district leaders approved updates to a plan to close achievement gaps and significantly increase the percent of students who pass mandatory North Carolina K-12 exams each year. They have goals to make improvements in key subjects — particularly in test results among students who are Black or Latino.
The plan comes after months of discussion by district administrators and board leaders.
Learn more about the effort with the Observer's Anna Maria Della Costa.
That's all for today, folks. If you don't already, subscribe to The Charlotte Observer here. If you're already a subscriber (thanks!), download our iOS or Android app to get connected.
Stay updated with us at charlotteobserver.com, and follow along on Twitter and Instagram to see more from us. Thanks for reading!
Did someone forward this newsletter to you? You can sign up here.
'Wheel of Fortune' contestant Charlene gets her Audi after narrowly missing out on show
Wax Dynasty Promotes Use Of The Kling Metaverse For The Unsalaried And Stay At Home Moms
DSM: Transaction in Own Shares
Of course, Shiffrin offers, she's pondered what emotions could wash over her after she powers to the bottom of the Alpine skiing hill during the upcoming Beijing Games. Of course, Shiffrin explains, she can't possibly predict how overwhelming they might be. "It's still pretty painful to think about, so I don't think about it too much," the 26-year-old Shiffrin said in a recent video interview with The Associated Press.
After "Wheel of Fortune" contestant Charlene missed out on winning an Audi because of a timing rule, the car maker stepped in to make it happen.
Downing Strategic Micro-Cap Investment Trust Plc (the "Company")LEI: 213800QMYPUW4POFFX69Transaction in Own Shares20 January 2022 The Company announces that on 20 January 2022 it bought back 20,000 Ordinary Shares of £0.001 each in the capital of the Company, at a price of 72 pence per share. These shares will be held in treasury. Following settlement of this purchase the number of Ordinary shares in issue, Ordinary shares held in treasury (which do not carry any voting rights) and total voting
Santa Clarita, California, Jan. 20, 2022 (GLOBE NEWSWIRE) -- Wax Dynasty is drawing attention to a newly launched feature recently announced by the Kling Metaverse, a platform currently being developed by Kling.Finance, that is trying to empower unemployed and underpaid people around the world. Wax Dynasty is an online publication that regularly publishes informative news, analysis, and tutorial articles on a variety of topics related to cutting-edge blockchain technologies such as cryptocurrenc
Wind farms take £160m off electricity bills as gas prices soar
The cost of electricity has risen because the UK relies heavily on gas to keep the lights on.
SB1 gives control over schools to taxpayers, rather than parents and teachers
OpEd: School boards represent a much broader constituency with interest in our schools than school councils.
'In the name of God, go': the history of a speech that has brought down parliament and a prime minister
First uttered by Oliver Cromwell, the words David Davis used to ask Boris Johnson to step down have a storied past.
Lyft passenger ratings explained
Did you know that Lyft drivers rate their passengers, too? There are good reasons why, and here's ho to find yours — and improve it if need be.
Honduran man in Texas hired hit man to kill wife's mom, uncle amid divorce, feds say
He wanted to make his soon-to-be ex-wife "cry tears of blood," authorities say.
Where Kentucky basketball recruits ended up in the new 247Sports rankings for 2022
A couple of Kentucky's signees dropped in the latest update from the national recruiting website.
'There are no minor incursions': Ukrainian president rebukes Biden over remarks on Russian invasion
Ukrainian President Zelenskyy said "there are no minor incursions," a direct retort to Biden's remarks.
PURA Farmersville Hemp Partnership Income Potential Enhanced By ALKM Progress
Dallas, TX, Jan. 20, 2022 (GLOBE NEWSWIRE) -- Puration, Inc. (OTC Pink: PURA) today highlighted the recent progress of Alkame Holdings, Inc. (OTC Pink: ALKM) in light of PURA's 5% stake in ALKM. Earlier this week, PURA published a 2022 strategic overview detailing the company's plan to grow revenue and increase shareholder value by driving market wide demand for the "multitude of yet to be realized uses of hemp." PURA is building a marketing co-op under the brand name "Farmersville Hemp." PURA's
Footage Shows Atmospheric Pressure Waves Over Hawaii After Tonga Eruption
An observatory in Hawaii captured atmospheric pressure waves created by the eruption of the Hunga Tonga-Hunga Ha'apai volcano on January 15.The Gemini Observatory in Hawaii was 5,000 kilometers (3,000 miles) away from the eruption when it captured the atmospheric pressure waves on three different cameras. They are the "faintly red waves" seen in the footage, NOIRLab explained.The Hunga Tonga-Hunga Ha'apai volcano erupted on January 15, triggering a tsunami on the South Pacific nation of Tonga with waves up to 15 meters, according to information released by the Tongan government. At least three people were killed and dozens of properties were damaged across the islands. Credit: NOIRLab via Storyful
St. John's airport has plan until Saturday, but uncertainty remains for some travellers
The St. John's International Airport says it has a plan in place to continue normal operations until at least 8 a.m. Saturday, amid an ongoing labour dispute which forced the cancellation of most commuter traffic there earlier this week. In a tweet posted Thursday afternoon, the airport is still working through the mediation process to resolve current issues between it and its staffed firefighters. The dispute between the airport authority and its fire staff came to a head on Tuesday afternoon.
GL Announces Simulation of Location Based Services in Mobile Networks
Location Services (LCS) Network Architecture Location Services (LCS) Network Architecture GAITHERSBURG, Md., Jan. 20, 2022 (GLOBE NEWSWIRE) -- GL Communications Inc., a global leader in telecom test and measurement solutions, addressed the press regarding their Location Services (LCS) Test Suite to support emulation of location services on GSM, UMTS, and LTE networks. "3GPP legacy technologies (GSM, UMTS and LTE) support LCS architecture for positioning mobile devices. Though there are a massive
FortisBC proposes to provide 100 per cent renewable gas to all new homes
Under a new proposal put forward by FortisBC Energy Inc. (FortisBC) to the British Columbia Utilities Commission (BCUC), every newly constructed home connecting to the gas system would automatically receive 100 per cent renewable gas1 for the lifespan of the building. The approval of this proposal would mark a new era in the evolution of the company's renewable energy programs.
Tayshia Adams Exits Bachelor Nation Podcast Click Bait as Tia Booth Steps in as New Co-Host
Tayshia Adams has departed her position as a co-host on Bachelor podcasts Click Bait and Bachelor Happy Hour


Wii remake of the classic PS2 horror game Fatal Frame II: Crimson Butterfly. Combines the plot of the original release with the technical improvements and gameplay changes brought to the franchise in Fatal Frame IV: Mask of the Lunar Eclipse.
Sisters Mio and Mayu Amakura visit their favourite childhood spot one last time before the construction of a dam will drown the entire area. As they walk through the woods they find themselves stumbling across an ancient town, populated only by the ghosts of its former inhabitants.


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Video shows man steal wrecked vehicle from dealership body shop
By Maria Salazar, FOX 26 News
HOUSTON (Fox 26) - The Houston Police Department needs help identifying a man captured on surveillance video leaving a car dealership's lot with a customer's wrecked Jeep Compass.
The incident happened on Saturday shortly before 4 p.m. at the Mac Haik Dodge Chrysler Jeep Ram dealership on the North Freeway. The dealership's sales department was still open, but the body shop was closed.
Jeffrey Goss says the stolen sport utility vehicle belonged to him. He thought things were looking up on Monday morning when he got a text from the dealership saying he car would be ready for pick-up at the end of the day. An hour later, he says he got a call from the dealership to inform him his car was stolen.
"This is a very random incident," says Shaun Jones, body shop manager with Mac Haik Dodge Chrysler Jeep Ram. "We do everything we can to keep vehicles safe and this could have happened to anybody."
In the surveillance video, a man is seen crawling under a garage door. He then opens another garage door while driving away in a Jeep Compass with front end damage. He steps out of the car to close the garage door and then gets back in the SUV and drives away in it.
"In watching him in the video, it looks like he just didn't have a care in the world," adds Jones. "I mean, didn't care of anybody saw him. He had a mission and that's what he was here to do."
Jones also says he has worked at the dealership for almost a decade and has never had a vehicle stolen from the body shop.
"Out of the thousands of vehicles on this lot that are new and driveable, why would you take something missing front end parts, having suspension damage, and just looking like a train wreck?" asks Jones. He says he believes the man in the video was tired of walking and used the car to get somewhere and likely abandoned it arriving or nearly arriving to his destination.
Jones adds that the SUV cannot be too far from dealership and spent Monday afternoon driving around the area to see if he could find it. Jones didn't have any luck but he hopes someone else will recognize the SUV and the man in the video.
"I hope the guy gets caught," says Jones. "People entrust us with their vehicles." He says the keys to vehicles in the body shop are usually left inside the cars but now he's considering locking them up when the shop is closed.
"You'd never think somebody's going to steal a car taken apart," Jones tells FOX 26 News.
Anyone with information on the Jeep Compass or the man in the video can leave a tip with Crime Stoppers of Houston by phone at 713-222-8477 (TIPS) or contact the Houston Police Department Auto Theft Division at 713-308-3500 or by email at HPDAutoTheft.Division@HoustonPolice.Org.


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Sunday 8 July 2018
'Worst Human Traffickers' Include Russia, Belarus, Iran, Turkmenistan
In a new report, the U.S. State Department says Belarus, Iran, Russia, and Turkmenistan remain among the worst offenders of human trafficking and forced labor.
Analysis: Did The Army That Gave Birth To Yugoslavia Also Destroy It?
A new report out of Belgrade itself suggests that the Yugoslav Army was less a bystander or victim of the breakup of Yugoslavia than an instrument of its demise. (The views expressed in this blog post do not necessarily reflect those of RFE/RL.)
Kosovo, Albania Open Funds To Help Soccer Players Pay Fines
Leaders of Kosovo and Albania have said they are collecting money to pay fines that two Switzerland soccer players received for making a pro-Kosovo gesture when the celebrated their team's victory over Serbia last week.
Swiss Players' Pro-Kosovo Celebration Triggers Fines But No Ban From Soccer
Soccer's world governing body FIFA has fined two Switzerland players for making politically and ethnically suggestive hand gestures to celebrate World Cup goals against Serbia, but the two were cleared to continue playing soccer.
Thaci, Vucic Hold 'Difficult' Talks On Normalizing Kosovo-Serbia Ties
Kosovo President Hashim Thaci and his Serbian counterpart, Aleksandar Vucic, came together in the Belgian capital on June 24 for EU-mediated talks aimed at normalizing bilateral relations.
FIFA To Probe Kosovo-Tied Players For Albanian Flag Gesture
Soccer's international governing body says it has initiated an investigation into reports of apparent politically tinged celebrations by two ethnic-Albanian members of Switzerland's World Cup squad.
Kosovo-Tied Swiss Players Criticized For Albania Gesture At World Cup Game
Two players with the Swiss national soccer team have sparked controversy for apparently making a political gesture after scoring goals in the team's 2-1 victory over Serbia in the 2018 World Cup on June 22.
Kosovo Celebrates Swiss Victory Over Serbia In The World Cup
People in Kosovo's capital, Pristina, came out into the streets on June 22 to celebrate the victory of Switzerland's national team over Serbia in a FIFA World Cup match in Russia. Swiss players of ethnic-Albanian origin Granit Xhaka and Xherdan Shaqiri scored in Switzerland's 2-1 win.
Switzerland Goals By Shaqiri, Xhaka Beat Serbia At World Cup
Goals by ethnic Albanians Xherdan Shaqiri and Granit Xhaka led Switzerland to a 2-1 victory over Serbia, dashing the Balkan squad's hope of quickly clinching a place in the next round in the World Cup.
Kosovo Battles For Recognition
A dispute over a claim that Liberia has renounced its recognition of Kosovo underscores Serbia's stubborn refusal to recognize Kosovo's statehood.
Kosovo's Thaci Wants 'Historic Deal' With Serbia
Kosovar President Hashim Thaci has pledged to continue dialogue with Serbia and reach a comprehensive, legally binding agreement on normalizing relations between Pristina and Belgrade.
Kosovars Make Splash With White-Water Inner Tube Race
Adrenalin junkies riding inner tubes drew weekend crowds to Prizren's river banks and bridges, in the city's annual "nontraditional" race.


Why do dogs jump up? A plausible explanation arises from their ways of communicating with each other. A puppy greeting an adult dog often licks the adult's muzzle — a polite, deferential behavior. Dogs, of course, descend from wolves, among whom muzzle-licking is how pups get the grownups to regurgitate food for them. Domestic dogs rarely nourish puppies this way, but muzzle-licking has survived, maybe because deferential behaviors are handy for a social animal. Think of humans saying "No, after you." Muzzle-licking is also an appeasement behavior — something you trot out to de-escalate a fight. A human might lift up his hands, palms toward the person he's arguing with.
Puppies in human households try to lick the weird, flat, usually bald body part we have instead of a muzzle. When a cute little puppy jumps up to lick face, many people can only say "Awwww!" Hey presto! Jumping up has been rewarded. The puppy's natural inclination is now a learned behavior. Too bad for the dog when he's nine months old, bigger and less cute, muddying the pinstripes and knocking Granny to the ground.
Paying attention to a dog only when all four paws are on the floor can work well, if jumping isn't well entrenched and if everybody who deals with the dog follows the rules. Unfortunately, much of humanity will get busy undermining you. "I don't mind your puppy jumping up," they say, while you tear your hair out. Or they get all disciplinarian, maybe kneeing the dog in the chest. That is not only mean but counterproductive, because dogs often respond by trying to appease. Since humans are usually taller than dogs, reaching our muzzles to lick them involves jumping up.
Fortunately, polite greetings are easily taught – most easily, of course, if you start out early so you aren't trying to undo a well-practiced habit. For simplicity I'll just speak of dogs, but the training tips here apply to puppies too.
When you're training your dog to greet politely and stop jumping up, it's easiest to work with two people. One person will hold the dog's leash. The dog should have plenty of room to sit, stand, or lie down comfortably, and to move within a radius of a couple of feet. The second person can be anyone your dog likes.
With the dog's human friend about a dozen feet away, the person holding the leash asks the dog to sit.
As soon as the dog does so, the dog's friend starts to approach. Because the dog likes this person, the approach will reward the sit. And, because the dog likes this person, he'll probably get up and move toward her.
At that moment, the approaching person stops dead, turns away from the dog, and retreats.
The person holding the leash cues the dog to sit.
As soon as the dog sits, the friend again approaches.
If the dog gets up, the friend stops and retreats again.
Usually, after two or three tries, the leash holder can stop giving the cue to sit. Instead, count to 5 slowly, in your head. Given a few moments to think, most dogs will experiment – what was it that got my friend to come closer? Eureka! That is the first step toward a dog who sits spontaneously in order to get people to approach.
The self-control problem isn't solved yet — the bouncier the dog, the more tries you'll need. Once the dog holds his sit till his human friend has reached him, have a love party. The leash holder can tell the dog it's okay to get up at this point. But if the dog begins to jump, the friend should instantly back away. Notice how simple and clear the communication is. The consequence of sitting politely is that someone you like comes closer. The consequence of jumping up is that she goes away.
Here's a hot tip for bouncy dogs: keep the love party low-key, and drop a few treats on the ground – the dog can't troll for smorgasbord and jump at the same time . Speaking of treats, the main reward for your dog in this training scenario is the chance to say hello. Feel free, though, to slip him treats as he holds his sit. You can phase out the treats over time. Also, any dog will find it easier to stay put if he's had plenty of exercise that day. Finally, if your dog's really having trouble, work on a sit-stay without the greeting component first.
When your dog's heinie is glued to the ground till you okay him to get up, start the whole process over again minus the leash. If the dog breaks his sit more than once or twice and goes over to the approaching person, go back and practice some more with the dog leashed.
Finally, while your dog is learning to sit patiently as fake guests come in, don't set him up to practice exactly the opposite with real guests. Having company? Crate your dog, leash him, or put him behind a baby gate till everyone's settled and he's calmed down. Then bring him out, on leash, to say polite hellos.


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text:
\section{Introduction}
\begin{figure*}[t]
    \centering
    \includegraphics[width=1.0\linewidth]{images/intro/intro_figure_v5.pdf}
    \vspace{-0.3cm}
    \caption{\textbf{Comparison of our CAD model alignment approach to ROCA \cite{roca}.} For each pixel of the detected object ROCA predicts the 3D normalised object coordinates (NOCs) in a canonical, normalised frame. However, those predictions are susceptible to systematic offsets (see Front View and Side View). While the reprojected NOCs match the image, the corresponding CAD model alignment does not. Our approach in contrast reprojects points and surface normals sampled from the CAD model in an initial pose into the image and uses those to predict pose updates. By iteratively updating the pose and reprojecting our system achieves precise CAD model alignments.}
    \vspace{-0.2cm}
    \label{fig_intro}
\end{figure*}
Previous work on shape and pose prediction can be classified into two different types of methods relying either on shape generation \cite{meshrcnn,pixel2mesh,total_3D_understanding} or shape retrieval \cite{mask2cad,patch2cad,geometric_correspondence_fields,roca}. Generative approaches usually struggle to produce realistic object shapes.
For methods relying on shape retrieval one of the key challenges is to align the retrieved CAD model to the object detected in the image \cite{mask2cad,patch2cad,geometric_correspondence_fields,roca}. Many existing approaches directly regress object poses from the 2D features of the image \cite{mask2cad,patch2cad,vid2cad,engelmann2020points}. However, this produces approximate poses rather than accurate alignments. ROCA \cite{roca} follows a more geometric approach in which they predict normalised object coordinates (NOCs) \cite{vitruvian_manifold}, dense correspondences from 2D pixel to 3D points in a canonical object space, that are used to compute the object pose. The fundamental issue with learning NOCs is that it is unclear how  different shapes should be registered with each other. This means that the NOCs do not generalise well between CAD models and predicting them often fails with a systematic offset leading to a displacement in the final alignment (see Figure \ref{fig_intro}).
Rather than using NOCs we propose a sparse, render-and-compare approach.
We combine 2D image information including sparse depth and surface normals along with RGB colors with 3D CAD model information. Specifically, we initialise a CAD model in a generic pose and reproject points and surface normals sampled uniformly from its surface onto the image plane.
This combined information is used by our pose update prediction network, SPARC-Net, to estimate a 9-DoF pose update.
After adding the predicted pose update to the initial pose we reproject the CAD model again and estimate the next pose update step. Repeating this procedure we obtain the final pose in just three iterations.\\
Having access to estimated normal and depth values from the image and reprojected normals and depth from the CAD model allows the network to evaluate the current pose and predict an accurate pose update by easily comparing observed (image) and projected (CAD model) information. This is in contrast to other approaches that do not make use of any shape information when predicting object poses
\cite{mask2cad,patch2cad} or that rely on shape encodings
\cite{roca} which seems to be a more difficult learning task than using render-and-compare.
Note also that because of the render-and-compare our approach does not require the ability to register different CAD models with each other nor for the network to memorise 3D shapes.\\
We choose the Perceiver \cite{perceiver} architecture over traditional CNNs for the pose prediction network as Perceivers \cite{perceiver} allow for an efficient processing of the sparse object reprojection as they do not require a full, image-sized input. Also Perceivers \cite{perceiver} have linear time and memory complexity in terms of input as opposed to traditional transformers \cite{attention_all_need}. Not only do sparse inputs reduce the memory and network complexity, but we also show that they improve the alignment accuracy by avoiding overfitting.
Using our approach we improve upon the state-of-the art performance on the challenging real-world dataset ScanNet \cite{scannet} from $25.0\%$ instance alignment accuracy to $31.8\%$ instance alignment accuracy.\\
\textbf{Our contributions include:}
\begin{itemize}
    \item a \textbf{novel, sparse, render-and-compare method} that achieves state-of-the-art results in CAD model alignment from a single RGB image
    \item a \textbf{demonstration of} how 3D CAD model information and 2D image information can be effectively combined with \textbf{early-fusion}
    \item \textbf{highlighting that sparse inputs improve alignment accuracy} while at the same time \textbf{significantly decreasing memory and compute complexity}.
\end{itemize}

\vspace{-0.2cm}

\section{Related Work}\vspace{-0.2cm}
In this section we discuss relevant works including shape estimation from a single image, CAD model retrieval and alignment and efficient transformer architectures.\\
\textbf{Shape estimation from a single RGB image.}
Most works on shape estimation from a single image are structured such as to use an RGB image as input to a neural network and directly predict a 3D shape using some particular representation. Various representations have been explored ranging from voxels \cite{voxels} to point clouds \cite{point_set,pointclouds}, meshes \cite{pixel2mesh,meshrcnn,TMN,total_3D_understanding}, packed spheres \cite{point_set}, binary space partitioning \cite{binary_planes}, convex polytopes \cite{polytopes}, signed distance fields \cite{sdf} to other implicit representations \cite{nerf}. However, this is a difficult learning task and regardless of the representation chosen most approaches struggle to predict realistic shapes. Because of these issues we use a retrieval-based method.\\
\textbf{CAD model retrieval and alignment.}
Rather than generating shapes a second class of approaches estimates 3D shapes by retrieving from large-scale CAD model databases \cite{chang2015shapenet}. The large number of available CAD models ensures that appropriate CAD models can be retrieved which can reconstruct the scene in a clean and compact representation that can be easily consumed for downstream applications. Existing approaches differ significantly in their procedures for aligning the retrieved CAD models to the image. Mask2CAD \cite{mask2cad} as well as \cite{patch2cad,vid2cad} simply regress the object pose from image features. However, this produces inaccurate pose estimates and requires the network to memorize every CAD model shape, consequently performing poorly for unseen CAD models. \cite{langer_leveraging_shape} explicitly leverages the geometry of the retrieved CAD model by estimating 2D-3D keypoint matches but depend on accurate segmentation masks and require exact correspondence between CAD model and the object observed in the image. ROCA \cite{roca} learns dense correspondences between 2D pixels and 3D object coordinates in a normalised, canonical frame and use those for computing the object pose. While these dense correspondences are more robust than sparse ones, they often fail systematically, leading to constant offsets in the pose alignments (see Supp. mat.).\\
Another class of methods uses render-and-compare to iteratively update pose estimates  \cite{geometric_correspondence_fields,Im2CAD}. These tend to be more precise, but rely on good pose initialisation \cite{geometric_correspondence_fields,Im2CAD}.
 Traditionally these have been very slow due to the time consuming rendering process and the large number of renderings required.
 The large number of renderings is needed as existing render-and-compare works for shape and pose estimation learn a comparison function which they directly minimise at test time using gradient descent which requires a large number of steps \cite{geometric_correspondence_fields,Im2CAD} (on the order of 100s to 1000). In spirit our approach is most similar to the render-and-compare approaches. However, the advantage of our method is that it does not require rendering of the full object, but just a simple reprojection of a small amount of 3D points (e.g. 100,see \ref{sec_ablation}), and it directly learns pose updates rather than a comparison function, making our approach a lot faster than \cite{Im2CAD,geometric_correspondence_fields}.\\
\textbf{Efficient transformer architectures.}
In recent years Transformers \cite{attention_all_need} have been used for a range of different computer vision tasks \cite{vit,video_bert,image_transformer,sceneformer}. However, the all-to-all attention mechanism used in classical transforms suffers from a quadratic scaling problem. \cite{perceiver,perceiver_io,hierachial_perceiver} are one line of work aiming to make transformers more efficient and enabling them to deal with larger inputs. They achieve this by using cross-attention from the inputs to a small set of latent units and subsequently only perform all-to-all attention in this smaller latent space.

\vspace{-0.2cm}
\section{Method}\vspace{-0.2cm}
\begin{figure*}[t]
    \centering
    \includegraphics[width=1.0\linewidth]{images/method/method_v11.pdf}
    \vspace{-0.3cm}
    \caption{\textbf{Method.}
    (i) Given an RGB image we predict per pixel surface normals $\mathbf{N}_{Img}$ and depth $\mathbf{D}_{Img}$ (2D image information) and use bounding box and CAD model retrievals from \cite{roca} (see Sec. \ref{sec_object_detection}). (ii) We sparsely sample RGB colors, $\mathbf{N}_{Img}$ and $\mathbf{D}_{Img}$ from three different regions (the reprojected CAD model points, the bounding box and the whole image), stack them and add pixel coordinates $(u,v)$ and a token $\tau$ allowing the network to distinguish between different input types. 3D points and surface normals are sampled from the CAD model in an initial canonical pose and reprojected into the image plane (see Sec. \ref{sec_input_fusion}). 2D image information, 3D CAD model information and extra information is combined to form the input to the pose prediction network, SPARC-Net, predicting pose update steps $ \Delta \textbf{T}, \Delta \textbf{R}, \Delta \textbf{S}$ and rotation classification score $c$. Based on the prediction the pose is updated, the CAD model sparsely rendered and the next pose update is predicted (see Sec. \ref{sec_method_pose_update}).}
    \vspace{-0.3cm}
    \label{method_fig}
\end{figure*}
This section explains the key steps of our method. In a first step, we perform object detection as well as surface normal and depth estimation in an image.
In a second step, we sample depth and normal values from an image and combine them with reprojected depth and surface normals sampled uniformly from a CAD model. Finally, in a third step, we iterate the refinements of the 9-DoF initial pose of the CAD model, partially recomputing sparse inputs of step two for every refinement.
\vspace{-0.2cm}
\subsection{Object Detection, Normal and Depth Prediction}
\label{sec_object_detection}
As a first step we perform 2D Object detection, including bounding box and category prediction. The category prediction determines the class of CAD model that is retrieved while the bounding box allows us to initialise the CAD model pose (see Sec. \ref{sec_experimental_setup}) and guide the point sampling (see Sec. \ref{sec_input_fusion}).
We use the same object detections and CAD model retrievals as ROCA \cite{roca} for exact comparability. However, any other method could be used as well. Further we estimate per pixel surface normal $\mathbf{N}_{\text{Img}}$ and depth values $\mathbf{D}_{\text{Img}}$ as these contain crucial geometric information that can be used for precise pose predictions.
For both surface normal and depth estimation, we use a light-weight convolutional encoder-decoder architecture from \cite{GB-mono-2018-densedepth}. The training losses are the same as the state-of-the-art works \cite{GB-SNfromRGB_21_BAE} for surface normal estimation and \cite{Bae_2022_CVPR_depth} for depth estimation. We use ground truth surface normals provided by \cite{GB-SNfromRGB_19_FrameNet} and ground truth depth as provided by ScanNet \cite{scannet} (for details see Supp. mat.). When training the surface normal and depth network the train and test split used for evaluating SPARC-Net is respected.

\vspace{-0.2cm}
\subsection{Input Fusion}
\label{sec_input_fusion}
When attempting to estimate CAD model pose one is presented with two different kinds of information: 2D image information and 3D CAD model information. We fuse the two by sampling 3D points and corresponding surface normals from the CAD model and reprojecting those into the image plane. Comparing the reprojected surface normals and the depth associated with the reprojected point to depth and surface normals estimated from the 2D image allows a network to easily evaluate the current pose and predict a pose update based on this comparison.\\
\textbf{2D image information.}
We stack RGB colors and predicted surface normals $\mathbf{N}_{\text{Img}}$ and depth values $\mathbf{D}_{\text{Img}}$. However, rather than using the entire image as input we sparsely sample pixels from three selected regions. We sample $N_{\text{reproj}}$ pixels onto which CAD model points are reprojected (see paragraph ``3D CAD model information''), $N_{\text{bbox}}$ pixels inside the bounding box and $N_\text{context}$ pixels from the entire image.
Respectively, these provide information on whether the current pose matches the image, what the pose update should be and global context.
In Fig. \ref{iterative_refinement}b and Tab. \ref{table_ablation} we demonstrate that sampling image information sparsely reduces overfitting, leading to a better alignment accuracy, and greatly reducing memory consumption and network complexity (see Sec. \ref{sec_ablation}). For each of the sampled pixels containing color, depth and surface normal values we add the pixel coordinates $(u,v)$ and a token $\tau$ (to allow the network to distinguish between different types of inputs) and stack them to a $(N_{\text{reproj}} + N_{\text{bbox}} + N_\text{context}) \times (3 + 3 + 1 + 2 + 1)$ dimensional tensor as seen in Fig. \ref{method_fig}.\\
\textbf{3D CAD model information.}
We represent the CAD model as a collection of $N_{\text{CAD}}$ 3D points sampled uniformly from the object surface. We simply reproject 3D object points and their surface normals into the image plane which reduces the rendering operation to a perspective projection using a single matrix multiplication. The intuition behind this idea is that for texture-less CAD models almost all information is contained in the 3D shape. Hence there is no need for a full rendering pipeline that takes into account material, lighting, textures or visibility\footnote{While reprojecting all CAD model points into the image plane ignores potentially important occlusion effects we found SPARC-Net to perform well regardless. We have also tried to add information about whether a 3D object point is occluded or not, but did not observe any improvement in performance.}.
We stack reprojected surface normals $\mathbf{N}_{\text{CAD}}$ and the computed depth values $\mathbf{D}_{\text{CAD}}$ with their pixel coordinates and a token $\tau = 3$. Padding this tensor with zeros as RGB values we obtain a $N_\text{CAD} \times 10$ shaped tensor.\\
\textbf{Extra information.}
Additionally, we encode the bounding box information by sampling 10 points from each of the sides of the bounding box and inputting their pixel values  with a different token $\tau = 4$ (padding extra dimensions with 0's). We also directly input the initialised pose consisting of translation $\textbf{T}$, rotation parameterised as quaternion $\textbf{Q}$, scale $\textbf{S}$ and the CAD model ID encoded as a binary vector, each padded with 0's and a unique token. Finally, we concatenate the three different blocks containing image, reprojected CAD model and extra information to form a ($N_{\text{reproj}} + N_{\text{bbox}} + N_\text{context} + N_{\text{CAD}} + N_\text{extra}) \times 10 $  = ($N_\text{input} \times 10)$ dimensional tensor. This tensor is Fourier encoded with 64 frequency bands with a maximum frequency of 1120 (same as original Perceiver \cite{perceiver} applied to point clouds) resulting in a $N_\text{input} \times (10 + 64 * 2 + 1) = N_\text{input} \times C_\text{input}$ tensor which serves as the network input described in the next section.

\vspace{-0.2cm}
\subsection{Pose updates and Iterative Refinement}
\label{sec_method_pose_update}
Combining image information and CAD model information in the image plane allows the network to easily evaluate a given pose and predict a refinement based on this evaluation. We repeat this process $N_\text{iter}$ times allowing the network to refine its own predictions. Specifically, given an initial pose ($\textbf{T},\textbf{Q},\textbf{S}$) and all combined information explained in Sec. \ref{sec_input_fusion} we use a Perceiver network \cite{perceiver} to predict refinement steps ($ \Delta \textbf{T}, \Delta \textbf{Q}, \Delta \textbf{S}$) such that ($ \textbf{T} + \Delta \textbf{T}, \textbf{Q} \cdot \Delta \textbf{Q}, \textbf{S} + \Delta \textbf{S}$) is close to the correct pose $(\textbf{T}_{\text{gt}},\textbf{Q}_\text{gt},\textbf{S}_\text{gt})$ = ($\textbf{T} + {\Delta \textbf{T}}_\text{gt},\textbf{Q} \cdot {\Delta \textbf{Q}}_\text{gt},\textbf{S} + {\Delta \textbf{S}}_\text{gt}$).
Similar to previous works \cite{mask2cad,patch2cad} we find that learning rotations over the full, non-euclidean rotation space is difficult. We therefore follow a coarse-to-fine approach where we simultaneously train the network to predict a binary classification $c$ whether an initial rotation lies within the correct $90^\circ$ rotation bin $c_\text{gt}$ around the vertical.
For classifying rotation we use a standard binary cross-entropy loss $L_{\mathrm{BCE}}$ and for learning the offsets we use the L2 loss
such that our loss function is given by:
\vspace{-0.2cm}
\begin{equation}
\label{loss_equation}
L_{\text {align }}=
w_{\text {c}} L_{\mathrm{BCE}}(c_{\text{gt}},c)
+
w_{\text {t}} L_{\mathrm{L2}}(\Delta \mathbf{T}_\text{gt},\Delta \mathbf{T})
+
w_{\text {s}} L_{\mathrm{L2}}(\Delta \mathbf{S}_\text{gt},\Delta \mathbf{S})
+
w_{\text {q}} L_{\mathrm{L2}}(\Delta \mathbf{Q}_\text{gt},\Delta \mathbf{Q}).
\end{equation}\vspace{-0.4cm}

At test time we apply SPARC-Net to four rotation initialisation that are $90^\circ$ rotated around the vertical. For each of those we predict the probability $c$ indicating whether the correct rotation lies within $\pm 45^\circ$ of the tested initialisation. For the initialisation with the highest estimated probability $c$ we subsequently predict the 9 DoF pose updates and iteratively rerender and refine the pose.

\vspace{-0.2cm}
\section{Experimental Setup}
\vspace{-0.2cm}
\label{sec_experimental_setup}
This section briefly describes the dataset used for training and testing our method, as well as the evaluation metrics used and the hyperparameters chosen.\\
\textbf{ScanNet dataset.}
Similar to \cite{mask2cad,patch2cad,total_3D_understanding,roca} we train and test our approach on the ScanNet25k image data \cite{scannet} for which \cite{scan2cad} provide CAD model annotation for a wide range of objects. This dataset contains 20k training images representing 1200 train scenes and 5k validation images from 300 different evaluation scenes. We train and test our method on the 9 categories with the most CAD model annotations covering more than 2500 distinct shapes.\\
\textbf{Evaluation metric.}
We follow the original evaluation protocol introduced by Scan2CAD \cite{scan2cad} which evaluates CAD model alignments per-scene. In the same way as ROCA \cite{roca} we transform predicted CAD model poses into ScanNet \cite{scannet} world coordinates and apply 3D non-maximum suppression to eliminate multiple detections of the same object from different images. A CAD model prediction is considered correct if the object class prediction is correct, the translation error is less than 20 cm, the rotation error is less than $20^\circ$ and the scale ratio is less than $20\%$.
We found that there was a bug in the original evaluation code introduced by \cite{scan2cad} which was subsequently used for evaluating \cite{roca,mask2cad}. When computing the scale error the formula $\text{s}_{\text{error}} = | \sum_{i=x,y,z} ( S_i / S^{\text{gt}}_i  - 1 )|$ was used instead of $\text{s}_{\text{error}} = \sum_{i=x,y,z}  | (S_i / S^{\text{gt}}_i)  - 1 |$ which allowed scale errors in different directions to cancel each other out. We corrected this mistake and reevaluated \cite{mask2cad,roca} (see Supp. mat.).\\
\textbf{Input details.}
For the main experiment we choose
$N_\text{CAD}=1000$ and use the reprojected points as samples from the 2D image such that $N_\text{reproj}=1000$. Further we use
$N_\text{bbox}=1000$ and $N_\text{context}=5000$ as also shown in Fig. \ref{method_fig}.\\
\textbf{Perceiver architecture.}
For the Perceiver \cite{perceiver} we set $N_\text{latent} = 128$ and $C_\text{latent} = 256$ and as depicted in Fig. \ref{method_fig} repeat three blocks of one cross attention layer followed by two self-attention layers with weight sharing between each of the layers in the three blocks.\\
\textbf{Train details}.
We train the SPARC-Net for 300 epochs using the LAMB \cite{lamb} optimiser (as used by the original Perceiver \cite{perceiver}) with learning rate 0.001. For the loss function in Eq.~\ref{loss_equation} we set $w_c = 0.5$, $w_t = 0.5$, $w_s = 0.5 $ and $w_q = 1$. We use a batchsize of 80. For more information on sampling and initialising poses at train and test time see the Supp. mat.\\
\textbf{Implementation Details}.
All code is implemented in PyTorch \cite{pytorch}. SPARC-Net was trained on a single TitanXp for 36 hours.
\vspace{-0.2cm}
\section{Experimental Results}
In the first part of this section we compare ourselves to the state-of-the-art approaches \cite{roca,mask2cad,total_3D_understanding}. In the second part, we investigate and ablate different key aspects of our system, including the 2D pixel sampling, the sparse 3D object representation, render-and-compare, the number of refinements used and the relevance of different input information.
\begin{figure*}[t]
    \centering
    \includegraphics[width=1.0\linewidth]{images/results/results_qualitative_main_v4.pdf}\vspace{-0.3cm}
    \caption{\textbf{Qualitative results on ScanNet \cite{scannet}.} Our sparse, render-and-compare approach allows for more precise CAD model alignment compared to ROCA \cite{roca}. Typical failure cases of ROCA include systematic failure when predicting normalised object coordinates leading to wrong object translations (row 3) and wrong scale predictions (row 4). Row 5 shows failure cases for both methods in complex scenes (left) and when object boundaries are not clearly identifiable (right).}\vspace{-0.3cm}
    \label{qualitative_results}
\end{figure*}

\vspace{-0.3cm}
\subsection{Main Results}
 Tab. \ref{table_main_results} shows that our approach outperforms all competing approaches in all object classes (except for ROCA on the class ``display''). Further we significantly improve both the class average alignment accuracy from 18.4\% to 24.9\% as well as the instance alignment accuracy from 25.0\% to 31.8\%. Visually comparing our predictions to ROCA \cite{roca} in Fig. \ref{qualitative_results} we note that the improvements are mainly due to better translation and scale predictions. ROCA \cite{roca} relies on predicting normalised object coordinates for estimating translation. However, due to difficulties in aligning and registering different CAD models to a canonical frame, predicting NOCs often fails with a systematic offset leading to an offset in the final alignment (see Supp. mat.). In contrast, our approach is independent of the existence of a canonical object frame as it directly compares a reprojected object to an image. Further, ROCA decouples the scale predictions from predicting rotation and translation which can produce very wrong alignments for bad scale predictions (see Fig. \ref{qualitative_results}).
 We also evaluate our system when using ROCA's rotation predictions as an initialisation as opposed to our own classified rotation bins. Here we observe a further improvement of our alignment accuracy. The reason why ROCA's rotation predictions are good is that they are computed geometrically from correspondences and are largely unaffected by systematic offsets in NOCs predictions and wrong scale predictions.

\renewcommand{\arraystretch}{1.1}

\vspace{-0.2cm}
\subsection{Ablation}
\label{sec_ablation}
Note that in addition to average class alignment accuracy and instance alignment accuracy we report $\mathbf{T},\mathbf{R},\mathbf{S}$ and $c$ accuracy in Tab. \ref{table_ablation} where the same evaluation protocol is used as described in Sec. \ref{sec_experimental_setup}, but rather than requiring $\mathbf{T}$, $\mathbf{R}$ and $\mathbf{S}$ to be correct at the same time only the quantity of interest is required to be correct ($c$ is considered correct if the binary rotation classification is correct). If not otherwise specified in the following ``accuracy'' or ``performance'' refers to instance alignment accuracy.

\begin{table}[t]
    \centering
    \resizebox{\textwidth}{!}{
    \begin{tabular}{c|ccccccccc|cc}

     Method & bathtub & bed & bin & bkshlf & cabinet & chair & display & sofa & table & \textbf{class} & \textbf{instance}\\ [0.5ex]
     \hline

     Number of Instances \# & 120 & 70 & 232 & 212 & 260 & 1093 & 191 & 113 & 553 & 9 & 2844 \\
     \hline

     Total3D-ODN \cite{total_3D_understanding}& 10.0 & 2.9 & 16.8 & 2.8 & 4.2 & 14.4 & 13.1 & 5.3 & 6.7 & 8.5 & 10.4 \\
     Mask2CAD-b5 \cite{mask2cad} & 7.5 & 2.9 & 24.6 & 1.4 & 5.0 & 29.9 & 13.1 & 5.3 & 5.6 & 10.6 & 16.7 \\
     ROCA \cite{roca} & 20.8 & 8.6 & 26.3 & 9.0 & 13.1 & 39.9 & \textbf{24.6} & 10.6 & 12.7 & 18.4 & 25.0\\
     \hline

    SPARC-Net (ours) & \textbf{25.8} & 25.7 & 24.6 & \textbf{14.2} & \textbf{20.8} & 51.5 & 17.8 & \textbf{28.3} & 15.4 & 24.9 & 31.8 \\
    SPARC-Net + ROCA rot init & 25.0 & \textbf{30.0} & \textbf{36.2} & \textbf{14.2} & 19.2 & \textbf{52.3} & 20.4 & \textbf{28.3} & \textbf{20.1} & \textbf{27.3} & \textbf{34.1}\\

    \end{tabular}}
    \caption{\textbf{Alignment Accuracy on ScanNet} \cite{scannet,scan2cad} in comparison to the state-of-the-art.}\vspace{-0.5cm}
    \label{table_main_results}
\end{table}
\noindent
\textbf{Image sampling.}
We compare sampling the entire image to sparse sampling and observe worse alignment accuracy when using the entire image ($25.0\%$ vs. $31.8\%)$ due to faster overfitting at train time (see Fig. \ref{iterative_refinement}b). We further simplify our sampling scheme and instead of sampling the image globally, the bounding box and the reprojected query, we use samples from just the bounding box, $N_{\text{bbox}} = 1000$. Surprisingly, we observe that we can recover almost the same alignment accuracy $30.1\%$ compared to $31.8\%$ before.
By traininig and testing with less than 1\% of the original number of pixel (image resolution 480 x 360) we reduce the memory by a factor of 100.
The complexity of the Perceiver \cite{perceiver} is given by
$\mathcal{O}(N_\text{input} N_\text{latent}) + \mathcal{O} (L N_\text{latent}^{2}) \approx \mathcal{O} (N_\text{input} N_\text{latent})$  where $N_\text{input} >> N_\text{latent}$, $N_\text{input} >> L$. When using the whole image as input $N_\text{input}$ is dominated by the number of pixels $N_\text{input} \approx 480 \times 360$. Therefore as $N_\text{latent} = 128$ and $L = 2$ (two self-attention layers following the cross-attention layer) sparse inputs also reduce the compute complexity by a factor of 100, greatly speeding up training and testing.\\
\textbf{Sparse CAD model representation.}
When reducing the number of points $N_{\text{CAD}}$ we observe that remarkably with just 100 points we obtain similar performance as with 1000 points (30.0\% vs. 31.8\%), showing that 3D shapes can indeed be represented very sparsely. However, as we further decrease the number of points we observe a rapid decline in performance (20.9\% for $N_\text{CAD} = 50$ and $4.2\%$ for $N_\text{CAD} = 50$. Interestingly, this decrease is almost entirely due to worse rotation predictions (see $\mathbf{R}$ accuracy $24.8\%$ compared to $67.9\%$). Intuitively, this makes sense as an extremely sparse point cloud has very little structure from which to predict rotation while translation and scale can still be predicted. Initialising those extremely sparse models with ROCA \cite{roca} rotation predictions we can still recover reasonable alignment accuracy of $24.0\%$ and $29.9\%$ for $N_\text{CAD} = 20$ and $N_\text{CAD} = 50$.\\
\textbf{Render-and-Compare.}
We test the assumption that Render-and-Compare is beneficial for precise pose predictions by considering two networks which are trained either on no 3D shape information but just the CAD model ID or for which the CAD model is always presented in the same canonical pose. The first is motivated by works (e.g. \cite{mask2cad,patch2cad}) that contain no explicit 3D shape information and the second by \cite{kanazawaHMR18} that perform iterative pose updates without explicit rerendering. Similar to before both of these networks fail to learn accurate rotation predictions (both for the classification and the refinement) therefore we only show results where we initialise poses with ROCA \cite{roca} rotation predictions. Here we note that using just the CAD ID results in a significant decrease in performance (21.0\%), whereas using 3D information but presenting the CAD model in the same canonical pose achieves $25.9\%$ instance alignment accuracy.\\
\textbf{Number of refinements.}
Training and evaluating our network for different number of iterations we observe a significant improvement when increasing the number of refinements from 1 ($26.4\%$) to 3 ($31.8\%$) and no more improvement for 5 refinements ($31.3\%$).

\begin{figure*}[t]
    \centering
    \includegraphics[width=1.0\linewidth]{images/results/refinement_visualisation_v4.pdf}\vspace{-0.3cm}
    \caption{ a) \textbf{Visualisation of refinements} in iterative render-and-compare. b) \textbf{Train and validation loss as well as validation accuracy} on the ScanNet dataset \cite{scannet,scan2cad}. When training on the whole image SPARC-Net overfits the training data more easily resulting in higher validation loss and worse instance alignment accuracy.}\vspace{-0.1cm}
    \label{iterative_refinement}
\end{figure*}
\begin{table}[t]
    \centering
    \resizebox{\textwidth}{!}{
    \begin{tabular}{c|ccccc|cccccc|cc|ccc|cccc}

    \textbf{Accuracy} & \multicolumn{5}{c}{\textbf{2D Image Sampling}} & \multicolumn{6}{c}{\textbf{3D CAD model points}} & \multicolumn{2}{c}{\textbf{R. and C.}} &\multicolumn{3}{c}{\textbf{N Refinement}} & \multicolumn{4}{c}{\textbf{Input Information}} \\
    \hline
& \makecell{$N_\text{reproj}=100$\\$N_\text{bbox}=100$\\$N_\text{context}=0$\\$N_\text{CAD}=100$} & \makecell{$N_\text{reproj}=0$\\$N_\text{bbox}=200$\\$N_\text{context}=0$\\$N_\text{CAD}=100$}& \makecell{$N_\text{reproj}=0$\\$N_\text{bbox}=1000$\\$N_\text{context}=0$\\$N_\text{CAD}=100$} & \makecell{$N_\text{reproj}=0$\\$N_\text{bbox}=0$\\$N_\text{context}=5000$\\$N_\text{CAD}=1000$} & \makecell{Whole img \\$N_\text{CAD}=1000$} & \makecell{20} & \makecell{20*} & \makecell{50} & \makecell{50*} & \makecell{100} & 1000 & \makecell{Just\\CAD\\ID*} & \makecell{Canon-\\ical\\pose*} & 1 & 3 & 5 & \makecell{No\\D} & \makecell{No\\N} & \makecell{No\\RGB} & \makecell{No RTS\\ or CAD\\ info} \\
\hline
\textbf{Class} & 12.9 & 12.7 & 23.9 & 14.8 & 20.3 & 3.5 & 17.7 & 15.9 & 24.9 & 23.1 & 24.9 & 15.0 & 20.2 & 16.6 & 24.9 & 25.2 & 15.0 & 16.6 & 24.7 & 22.2 \\
\rowcol \textbf{Instances} & 18.5 & 19.7 & \textbf{30.1} & 20.1 & \textbf{25.0} & \textbf{4.2} & \textbf{24.0} & \textbf{20.9} & \textbf{29.9} & \textbf{30.0} & \textbf{31.8} & \textbf{21.0} & \textbf{25.9} & \textbf{26.4} & \textbf{31.8} & \textbf{31.3} & \textbf{18.8} & \textbf{20.7} & \textbf{30.5} & \textbf{28.9} \\
\textbf{T} & 40.8 & 42.1 & 42.4 & 37.1 & 38.7 & 38.0 & 39.9 & 38.2 & 42.5 & 42.2 & \textbf{45.4} & 36.4 & 41.4 & 42.3 & \textbf{45.4} & 43.7 & \textbf{30.7} & 40.2 & 42.6 & \textbf{42.2} \\
\textbf{R} & 49.1 & 48.7 & 70.8 & 61.4 & 68.2 & \textbf{24.8} & 63.7 & 58.4 & 70.9 & 71.1 & \textbf{67.9} & 63.8 & 63.7 & 65.5 & \textbf{67.9} & 71.5 & 68.2 & \textbf{56.8} & 72.3 & 66.3 \\
\textbf{S} & 61.0 & 62.4 & 69.0 & 61.3 & 66.8 & 63.7 & 63.3 & 66.4 & 67.7 & 67.8 & 68.4 & 62.9 & 68.9 & 62.8 & 68.4 & 66.4 & 64.5 & 63.7 & 68.5 & 67.2 \\
\textbf{R class} & 70.7 & 71.3 & 75.2 & 69.7 & 72.9 & 53.4 & 76.4 & 68.9 & 77.4 & 75.6 & 75.9 & 77.0 & 76.3 & 74.8 & 75.9 & 75.6 & 73.0 & 74.5 & 76.1 & 74.4
\end{tabular}}

\caption{\textbf{Ablation.} We perform a number of different ablations as explained in detail in Sec. \ref{sec_ablation}. Bold numbers are the ones referred to in Sec. \ref{sec_ablation}. Note that a ``*'' indicates that ROCA \cite{roca} rotation predictions are used for initialising rotations. Our main experiment is listed twice under ``3D CAD model points $N_\text{CAD} = 1000$'' and ``N Refinements, $N = 3$'' for convenience. ``R. and C.'' stands for Render-and-Compare.}\vspace{-0.4cm}
\label{table_ablation}
\end{table}
\noindent
\textbf{Input modalities.}
Furthermore, we investigate the importance of the different information that is provided as input to the network. Here we find that both depth and normal predictions are crucial for SPARC-Net. Not providing depth predictions from the 2D image reduces the accuracy to $18.8\%$ while not providing normal predictions reduces it to $20.7\%$. We find that for depth this drop in performance is mainly due to worse $\mathbf{T}$ predictions ($30.7\%$ compared to $45.4\%$) whereas for the normals it is due to worse rotation predictions ($56.8\%$ compared to $67.9\%$) which is exactly as one would expect. In contrast, not providing RGB color only reduces the accuracy marginally to $30.5\%$. This makes sense as given depth and surface normal estimates color only adds very little information for shape alignments. When no extra information is provided the accuracy is reduced to $28.9\%$. The individual accuracies suggest that the network uses extra information to learn the distribution of object positions as we observe the largest decrease for $\mathbf{T}$ accuracy to $42.2\%$.\\

\vspace{-0.6cm}
\section{Conclusion}\vspace{-0.1cm}
We have proposed SPARC, a sparse render-and-compare approach for CAD model alignment from a single RGB image. We show how to effectively combine 3D CAD model information and 2D image information with early-fusion which helps our pose prediction network to estimate accurate pose updates. In this way we improve the state-of-the-art on ScanNet~\cite{scannet} from $25.0\%$ to $31.8\%$ instance alignment accuracy.
We demonstrate that using sparse 2D image information (less than 1\% of available pixels) reduces overfitting leading to better pose predictions and greatly reducing memory and network complexity. Furthermore, sparse input processing may bring even more benefits when dealing with sensory input that is naturally sparse such as LIDAR or event cameras.
In the future, we plan to expand this work to updating not only the estimated pose, but also the CAD model shape in order to alleviate the requirement of CAD models that are very similar to the objects in the image.

redpajama_set_name: RedPajamaArXiv


text:
Q: First call to ReactContext is setting the isLoading sate to false I have Component A and Component B that both uses the same ReactContext to fetch the data. Whichever component calls the context first, at the end of fetching the data, the Context sets the isFetchingData state to false.
Now, when the second component calls the context the isFetchingData state is already set to false. Therefore, it renders the component without waiting for the data.
To illustrate:
ComponentA => isFetchingData? true => getsData => sets isFetchingData to false. => renders component
ComponentB => isFetchingData? false => renders the component => getsData => sets isFetchingData to false (already false)
How can I address this?
Following is my code.
Context:
    const [allEmployees, setAllEmployees] = useState([]);
    const [isFetchingData, setIsFetchingData] = useState(true);

    useEffect(() => {
        getAllEmployees().then(
            //doing something
        ).then(employees => {
            setAllEmployees();
            setIsFetchingData(false);
        });
    }, [])

Component:
const ComponentB = () => {

    const {
        allEmployees,
        isFetchingData
    } = useContext(MyContext);

    if(isFetchingData) {
        return <p>'Loading'</p>; // it never hits this as its false
    }

    return (
    // if data is loaded render this
    );
};

redpajama_set_name: RedPajamaStackExchange


text:
import math
from copy import deepcopy
from six.moves import range
from esengine.exceptions import PaginationError, StopPagination

class Pagination(object):

    def __init__(self, iterable, page=1, per_page=10):
        """
        Initialize an iterator
        :param iterable: Payload (recommended), ResultSet or an iterator
        :param page:
        :param per_page:
        :return:
        """
        self.init(iterable, page, per_page)

    def init(self, iterable, page, per_page):
        page = int(page or 1)
        per_page = int(per_page or 10)
        if page < 1:
            raise PaginationError("Page is lower than 1")

        self.iterable = iterable  # noqa
        self.page = page  # noqa
        self.per_page = per_page  # noqa

        if hasattr(iterable, 'count'):
            self.total = self.total_size = int(iterable.count())
        else:
            self.total = self.total_size = len(iterable)  # noqa

        start_index = (page - 1) * per_page
        end_index = page * per_page

        if hasattr(iterable, 'search'):  # it is a Payload
            struct_bck = deepcopy(iterable._struct)
            # apply pagination
            total_size = iterable._struct.get('size')
            if total_size:
                self.total_size = int(total_size)  # noqa
            iterable.from_(start_index)
            iterable.size(per_page)
            self.items = iterable.search()
            # restore Payload state
            iterable._struct = struct_bck
        else:
            self.items = iterable[start_index:end_index]  # noqa

        if not self.items and page != 1:
            raise StopPagination("There is no items to paginate")

        if self.page > self.pages:
            raise StopPagination("Pagination Overflow")

    def count(self):
        """
        The minimum between search.count and specified total_size
        :return: integer
        """
        return min(self.total, self.total_size)

    @property
    def pages(self):
        """The total number of pages"""
        return int(math.ceil(self.count() / float(self.per_page)))

    def prev_page(self, inplace=False):
        """Returns a :class:`Pagination` object for the previous page."""
        if self.iterable is None:
            raise PaginationError('iterable is needed')
        if not self.has_prev:
            raise StopPagination("There is no previous page")
        return (
            self.__class__
            if not inplace else
            self.init
        )(self.iterable, self.page - 1, self.per_page)

    def backward(self):
        return self.prev_page(inplace=True)

    @property
    def prev_num(self):
        """Number of the previous page."""
        if self.has_prev:
            return self.page - 1

    @property
    def has_prev(self):
        """True if a previous page exists"""
        return self.page > 1

    def next_page(self, inplace=False):
        """Returns a :class:`Pagination` object for the next page."""
        if self.iterable is None:
            raise PaginationError('iterable is needed')
        if not self.has_next:
            raise StopPagination("There is no next page")
        return (
            self.__class__
            if not inplace else
            self.init
        )(self.iterable, self.page + 1, self.per_page)

    def forward(self):
        self.next_page(inplace=True)

    @property
    def has_next(self):
        """True if a next page exists."""
        return self.page < self.pages

    @property
    def next_num(self):
        """Number of the next page"""
        if self.has_next:
            return self.page + 1

    def iter_pages(self, left_edge=2, left_current=2,
                   right_current=5, right_edge=2):
        """Iterates over the page numbers in the pagination.  The four
        parameters control the thresholds how many numbers should be produced
        from the sides.  Skipped page numbers are represented as `None`.
        This is how you could render such a pagination in the templates:

        .. sourcecode:: html+jinja

            {% macro render_pagination(pagination, endpoint) %}

              {%- for page in pagination.iter_pages() %}
                {% if page %}
                  {% if page != pagination.page %}
                    {{ page }}
                  {% else %}
                    {{ page }}
                  {% endif %}
                {% else %}
                  …
                {% endif %}
              {%- endfor %}

            {% endmacro %}
        """
        last = 0
        for num in range(1, self.pages + 1):
            if num <= left_edge or \
               (num > self.page - left_current - 1 and
                num < self.page + right_current) or \
               num > self.pages - right_edge:
                if last + 1 != num:
                    yield None
                yield num
                last = num

    @property
    def meta(self):
        return {
            'total': self.count(),
            'pages': self.pages,
            'per_page': self.per_page,
            'page': self.page,
            'next_page': self.next_num,
            'previous_page': self.prev_num
        }

    def to_dict(self):
        return {
            "items": self.items.to_dict(),
            "meta": self.meta
        }

redpajama_set_name: RedPajamaGithub


From the May 2012 Ensign — Music by a Young Women choir from stakes in American Fork, Utah; Merrilee Webb, director; Bonnie Goodliffe, organist: "Come, Ye Children of the Lord," Hymns, no. 58, arr. Wilberg, pub. Jackman; "As Zion's Youth in Latter Days," Hymns, no. 256, arr. Kasen, pub. Jackman; "I Feel My Savior's Love," Children's Songbook, 74–75, "Beautiful Savior," Children's Songbook, 62–63, medley arr. Webb, unpublished (cello: Daphne O'Rullian); "High on the Mountain Top," Hymns, no. 5.
Words: Ralph Rodgers Jr.; K. Newell Dayley; Laurie A. Huffman; Anon.
From the May 2012 Ensign — Music by the Tabernacle Choir; Mack Wilberg and Ryan Murphy, directors; Andrew Unsworth and Clay Christiansen, organists: "High on the Mountain Top," Hymns, no. 5; "Praise the Lord with Heart and Voice," Hymns, no. 73; "You Can Make the Pathway Bright," Hymns, no. 228, arr. Wilberg, unpublished; "How Firm a Foundation," Hymns, no. 85; "Love Is Spoken Here," Children's Songbook, 190–91, arr. Cardon, unpublished; "Redeemer of Israel," Hymns, no. 6, arr. Wilberg, pub. Hinshaw.
From the May 2012 Ensign — Music by a combined choir from the Provo Missionary Training Center; Douglas Brenchley and Ryan Eggett, directors; Bonnie Goodliffe, organist: "Glory to God on High," Hymns, no. 67, arr. Manookin, pub. Jackman; "Lead, Kindly Light," Hymns, no. 97, arr. Wilberg, pub. Jackman; "Called to Serve," Hymns, no. 249; "Praise to the Man," Hymns, no. 27, arr. Wilberg, pub. Jackman.
From the May 2012 Ensign — Music by a priesthood choir from the Salt Lake university institutes; Hal W. Romrell, Craig Allen, and Dennis Nordfelt, directors; Richard Elliott, organist: "Jesus, Savior, Pilot Me," Hymns, no. 104, arr. Longhurst, pub. Jackman; "Carry On," Hymns, no. 255, arr. Durham, pub. Jackman; "Ye Elders of Israel," Hymns, no. 319; "Dear to the Heart of the Shepherd," Hymns, no. 221, arr. Beebe, pub. Larice.
From the May 2012 Ensign — Music by the Tabernacle Choir; Mack Wilberg, director; Clay Christiansen and Richard Elliott, organists: "Come, Ye Children of the Lord," Hymns, no. 58; "Praise to the Lord, the Almighty," Hymns, no. 72, arr. Wilberg, pub. Oxford; "Teach Me to Walk in the Light," Hymns, no. 304, arr. Wilberg, unpublished; "Rejoice, the Lord Is King!" Hymns, no. 66; "Let Us Oft Speak Kind Words," Hymns, no. 232, arr. Wilberg, unpublished; "Come, Thou Fount of Every Blessing," Hymns (1948), no. 70, arr. Wilberg, pub. Oxford.
From the May 2012 Ensign — Music by the Tabernacle Choir; Mack Wilberg and Ryan Murphy, directors; Linda Margetts and Bonnie Goodliffe, organists: "On This Day of Joy and Gladness," Hymns, no. 64, arr. Murphy, unpublished; "Come unto Jesus," Hymns, no. 117, arr. Murphy, unpublished; "Hope of Israel," Hymns, no. 259; "I Need Thee Every Hour," Hymns, no. 98, arr. Wilberg, unpublished.


text:
Катали́на Поно́р ( ; ) — румынская гимнастка, трёхкратная олимпийская чемпионка 2004 года, восьмикратная чемпионка Европы в 2004—2017 годах, многократный призёр чемпионатов мира. Наиболее успешно выступала на бревне и в вольных упражнениях.

Биография
Начала заниматься гимнастикой в четыре года. В 2002 году спортсменку заметили Октавиан Белу и Марианна Битанг, пригласив в национальную сборную.

Первого крупного международного успеха добилась в 2003-м году на чемпионате мира в Анахайме. Настоящим триумфом Понор стал 2004-й год. Она стала трёхкратной олимпийской чемпионкой в Афинах, трёхкратной чемпионкой Европы, а также выиграла золото в финале Кубка мира. В декабре 2007 года Понор была вынуждена объявить об уходе из спорта в связи с травмами.

Весной 2011 года Каталина вернулась к тренировкам и в национальную сборную. На летних Олимпийских играх 2012 в Лондоне помогла сборной Румынии квалифицироваться в командный финал, а также квалифицировалась в индивидуальных первенствах в финалы на бревне и в вольных упражнениях. В командном финале она получила 15,100 в опорном прыжке, 15,416 на бревне и 14,8 в вольных упражнениях и помогла своей команде завоевать бронзовые олимпийские медали. В финале на бревне по оценкам судей занимала 3-е место с результатом 15,066. Однако по удовлетворенному протесту США в итоге получила только 4-е место: бронзовая медаль в этом виде была присуждена Александре Райзман (был повышен коэффициент сложности программы американки, с 6,2 до 6,3). Сразу после этого завоевала серебряную олимпийскую медаль в финале по вольным упражнениям с результатом 15,2.

После Олимпиады 2012 года Понор не принимала участия в соревнованиях, но весной 2015, вместе с другой завершившей карьеру звездой румынской сборной Сандрой Избашей, заявила о намерениях вернуться в сборную перед Олимпийскими играми 2016. На чемпионате Европы 2016 румынка завоевывает две бронзовые медали. На Олимпийские игры в Рио-де-Жанейро у представительниц Румынии лишь одна квота, и 6 июля было объявлено, что эта квота достается Каталине Понор. Кроме того, Понор была выбрана знаменосцем на церемонии открытия. На Играх смогла пройти в финал в упражнении на бревне, но выступила в финале неудачно и стала лишь 7-й. Понор стала первой румынской гимнасткой выступившей на трех Олимпиадах. После Рио объявила о планах выступить на домашнем чемпионате Европы 2017, а также на следующей Олимпиаде в Токио, в 2020 году.

На домашнем чемпионате Европы 2017 в Клуж-Напока завоевала золотую медаль в упражнении на бревне, установив рекорд по количеству золотых медалей континентальных первенств на этом снаряде (пять побед).

5 октября 2017 года, после квалификационных соревнований чемпионата мира, объявила о завершении карьеры.

Примечания

Ссылки
 Catalina Ponor at Fédération Internationale de Gymnastique

Гимнасты Румынии
Олимпийские чемпионы от Румынии
Олимпийские чемпионы по спортивной гимнастике
Чемпионы летних Олимпийских игр 2004 года
Серебряные призёры летних Олимпийских игр 2012 года
Бронзовые призёры летних Олимпийских игр 2012 года
Гимнасты на летних Олимпийских играх 2004 года
Гимнасты на летних Олимпийских играх 2012 года
Гимнасты на летних Олимпийских играх 2016 года
Знаменосцы на летних Олимпийских играх 2016 года
Чемпионы Европы по спортивной гимнастике

redpajama_set_name: RedPajamaWikipedia


text:
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Universal Classics: 50 Cent, Lil Wayne, Eminem, Kanye West & Tupac Shakur
Universal Music has announced huge plans for diehard fans and supporters of 50 Cent, Lil Wayne, Eminem, Kanye West and Tupac ...
Kanye West Paid $3 Million To Perform For Kazakhstan President
It appears that rapper Kanye West had a great Labor Day weekend. It is being reported that Kanye was paid ...
Kanye West Performs "Blood On The Leaves" At 2013 MTV VMA's
Last night, Kanye West performed "Blood On The Leaves" a track from his Yeezus album at the Brooklyn's Barclays Center ...
Kanye West Confirmed To Perform BLKKK SKKKN HEAD At VMA's
This years MTV Video Music Awards which will be held on August 25th at the Barclay's Center and will feature ...
Kanye West & Rhymefest Start Chicago Youth Program
Chicago natives Kanye West and Rhymefest have paired up to for a great cause. The two have launched a music, ...
Kanye West Lucks Out After LAX Attack
Sat, 27 Jul 2013
Kanye West has one less thing to worry about after reports claim he will not be prosecuted for a recent attack ...
Kanye West Scuffle With Photographer Investigated
Tue, 23 Jul 2013
Us Weekly is reporting that rapper, Kanye West could be facing assault charges for the scuffle he had with a ...
"Watch The Throne 2″ Is A Go!!!
Hip-hop producer Mike Dean used Twitter to confirm that once again, Jay-Z and Kanye West are for sure making plans ...
Kanye West Confirms "Black Skinhead" Video Leak
"Black Skinhead", a track on the Kanye West album Yeezus which was reportedly posted on the official Website for rapper ...
Kanye West Moving Into Fashion
Award winning rapper Kanye West has had a lot of positive things going for him this month. The first with ...
T.I. & Kanye West Being Sued By Rock Band
Bloodstone, an R&B/Funk/Rock band that has a dislike for hip-hop music is suing Universal Records, T.I. and Kanye West. The lawsuit ...
Kanye West's Yeezus Album Sales #1 In U.K. & Austrailia
Many albums dropped June 18th and many were wondering who would come out on top. The answer to that question ...
Kanye West & Kim Kardashian Welcome Newborn Baby Girl
Sun, 16 Jun 2013
What a June's it's been so far for Kanye West. With preparations taking place for the release of his sixth ...
Kanye West "Yeezus" Album Leak, Def Jam On Manhunt
On Friday it was reported that Kanye's sixth studio album leaked out to the public. Def Jam is now on ...
Kanye West Groupie Leyla Ghobadi Fesses Up To Lying
The truth finally comes out. A Canadian model who claimed Kanye cheated on Kim Kardashian with her now confesses that ...
Kanye West Compares Himself To Steve Jobs & Dead Prez
Kanye West may claim that he doesn't do anything to get press, however his actions show that he desires the ...
Kanye West Cheated On Kim Kardashian With Model Leyla Ghobadi
According to the New York Post: Canadian model Leyla Ghobadi claims she had sex with Kanye West whiles still with pregnant Kim ...
Kanye West Premieres 3 New Songs At Governors Ball
The 2013 Governors Ball Music Festival held in New York featured new songs off of Kanye West's upcoming Yeezus album. Kanyee ...
Kanye West Asks Fans For Graffiti To Promote "Yeezus"
Artists such as J. Cole and Mac Miller are holding listening sessions, doing interviews and trying to generate buzz for ...
Kanye West In New Video Game "Kanye Quest 3030″
According to Kotaku.com, a video game version of Windy City rapper Kanye West will serve as the protagonist in a newly-released, ...
Chief Keef Confirms Appearance On "Yeezus"
Fellow Chicago rappers Chief Keef and Kanye West are unquestionably collaborating. In an interview with Elite Money Empire, Keef confirmed ...
Kanye West's "Air Yeezy II" May Arrive June 18th
Kanye West appears to be setting up to have a busy June, as the rapper not only will be releasing ...
Kanye West's "Yeezus" To Force Fans To Show Up June 18th
Kanye West is reportedly going old school with the upcoming release of his long-awaited Yeezus solo album by preventing any opportunity ...
Baltimore Police Cancels Screening Of Kanye West's "New Slaves"
Kanye West's multi-city broadcasts of his song "New Slaves" on buildings across the United States hit another drawback. ...
Kanye West's Project Continues Gaining Praise
Hip-hop star Kanye West's new untitled solo project continues to gain praise as G.O.O.D Music affiliate Travis Scott is the ...
Kanye West Upset Over "I Hit It First" Lyrics?
Is Kanye West ready to respond to Ray J after hearing "I Hit It First" over the weekend? Even though ...
Kanye West Facing New Copyright Lawsuit Over "Gold Digger"
Rapper Kanye West has found himself caught in the middle of another copyright infringement lawsuit thanks to his 2005 single ...
"I Am God": Rumored Name Of Kanye West's New Album
G.O.O.D. Music artist Kanye West is well known when it comes to making shocking remarks and pushing the limits and ...
Justin Timberlake Back Tracks From Kanye West Jab
Kanye West made headlines when he took the time to stop a performance to state, "I got love for Hov ...
Justin Timberlake Fires Back At Kanye West On Saturday Night Live
Two weeks ago, Kanye West caused a stir during a London performance after he said, "I got love for Hov, but I ain't ...
A$AP Rocky Loves Kanye's Style, Hates Lil Wayne's
Tue, 20 Nov 2012
Newer artist A$AP Rocky had an interview with DJ Drama, and one the topics was fashion. He said his fashion ...
Hurricane Sandy Benefit Concert
On 12/12/12, stars and celebrities of all kinds will be joining together for a concert that benefits those affected by ...
Don't Mention Reggie Bush around Kanye West
Mon, 15 Oct 2012
After leaving dinner in Miami with his boo Kim Kardashian, the couple was approached by a member of paparazzi whose ...
Kanye West & Kim Kardashian Look-a-Like Sex Tape???
Fri, 21 Sep 2012
Kanye West and his new fly girl Kim Kardashian have so much in common than you think, well Kanye has ...
2 Chainz Turns To Kanye West For Album Cover
In a recent interview with Billboard, 2 Chainz spoke about creating the album cover for his much anticipated Based on a T.R.U. ...
Jay-Z & Kanye West "Watch The Throne" Album First Week Sales
Jay-Z & Kanye West's "Watch The Throne" album, released on August 08, 2011, first week sales is in. According to ...
Kanye West Pays Tribute To The Late Gil Scott-Heron
Lots of friends and relatives have paid tribute to the late Gil Scott-Heron in New York, on June 2, 2011. ...
Kanye West Wins "Stronger" Copyright Lawsuit Case
Sun, 06 Mar 2011
Last week, Kanye West has been accorded the paternity of his (now we can say that!) hit single "Stronger" from ...
Jay-Z & Kanye West Hires A Hotel For Album Recording
New York Post reports Kanye West and Jay-Z have been recording together in high style at the Mercer Hotel this ...
Kanye West "My Beautiful Dark Twisted Fantasy" Album Sales
Mon, 29 Nov 2010
Kanye West's "My Beautiful Dark Twisted Fantasy" album, released on November 22, 2010, first week final sales is in. ...
Kanye West's New Album Cover Banned In The USA
This past sunday (October 17), Kanye West announced via his Twitter profile that his album cover for "My Beautiful Twisted ...
Kanye West's New Album Gets A New Release Date
Kanye West's new album gets a new release date… Kanye's new album which hasn't yet got a title, atleast ...
Drake "Thank Me Later" Receives U.S. Platinum Plaque
Drake goes US Platinum and receives a U.S. Platinum Plaque… At the Constitutional Hall on the D.C. during Drake's "Light, ...
Kanye West Signs Mos Def To G.O.O.D Music
Mon, 27 Sep 2010
Kanye West keeps signing Classic artists to his G.O.O.D Music record label roster. He has already signed Common, John Legend, ...


Don't miss out on this one bedroom, one bath condominium which is located just steps away from all Rittenhouse Square has to offer! This sunny, mid-rise unit has both city & sunset views, a kitchen with stainless steel appliances and granite countertops, a pantry, a hall closet, a spacious bedroom, and a bathroom with a window. Hardwood floors throughout the living area. Shared laundry and reasonable condo fees as well! This location is a quick commute to Rittenhouse Square, University City, 30th Street Station, Market Street and City Hall. Walk to Septa routes, cafes, shops, grocery stores, gyms, restaurants, the Schuylkill River Trail and museums. Condo fee includes cold and hot water, building insurance, trash removal and common area maintenance. Property has a dedicated heating & cooling unit as well.


The original idea here was to make an 8 string that isn't simply geared towards making metal but a wide array of genres with metal included. Sing you to sleep, bring the funk, djent your face off, it would excel with all these while looking the part.
I also really love the natural wood look. I found that when friends would come over who didn't play themselves they would especially like the look of the natural wood guitars. It's like a classy piece of furniture that happens to sound amazing. Once we had this basic design we knew we needed to make a 6 string too.
OK, I could talk about these for hours so maybe I'll just stop here... I'm so proud of these guitars.


The Gospel doesn't demand faith…The Gospel supplies faith! Faith is very important, but much simpler than most people think. Listen in and be effortlessly blessed!
Taste, experience His goodness and rejoice.
Is there a place of perfect peace? A place where you experience the security, safety and provision of His love? A place of all sufficiency in all things? Yes, yes and yes and it feels like heaven!
Transformation that will shockingly surprise you!