Answers.Body: <p>Short answer: No.</p>
  
  <p>Long answer: A neural network is a function that maps input data (e.g. a picture) to output data (e.g. probability that the picture contains a dog). What you propose does not seem like the sort of task this tool is suited for, though I'm not willing to claim that it can't be done.</p>
  
  <p>If you are interested in computer-generated artwork, I encourage you to learn about <a href="http://blog.aylien.com/introduction-generative-adversarial-networks-code-tensorflow/" rel="nofollow noreferrer">Generative Adversarial Networks</a> and <a href="https://www.youtube.com/watch?v=Oex0eWoU7AQ" rel="nofollow noreferrer">style transfer</a>.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T05:19:55.940Z
Answers.Text: You have only described a neural network as a classification tool.. what about reinforcement learning and regression-based nets?
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T15:52:19.000Z
Answers.Text: The use case doesn't change the fundamental concept of the net - it's still a function mapping input variables to output variables.
Answers.UserDisplayName: Jessica Alan
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T22:27:41.820Z
Answers.Text: Ok, am i able to map 3d coordinates from a 2d input? lets say i make a 3d object and screenshot it, can i map one to the other?
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-14T15:07:59.430Z
Answers.Text: So a network that maps a 2D representation of an object to its 3D vertices? That sounds feasible.
Answers.UserDisplayName: Jessica Alan
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-14T23:06:34.083Z
Answers.Text: ok cool im on to it!
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-12T23:14:43.410Z
Answers.LastActivityDate: 2017-06-12T23:14:43.410Z
Answers.UserDisplayName: Jessica Alan
Answers.Body: <p>Just like the other answer - it can't really be done like that. However, you might want to take a look at <a href="https://github.com/google/deepdream" rel="nofollow noreferrer">Google Deepdream</a>, which actually enhances images to look more like what they detected. E.g., if a cat is detected, it will make the picture more cat-like.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T07:55:37.087Z
Answers.LastActivityDate: 2017-06-13T07:55:37.087Z
Answers.UserDisplayName: Thomas Wagenaar
Answers.Body: <p>About the screenshot you mentioned in comments: don't forget that NN build the mappings from learning. With only one screenshot, you'll only be able to construct a NN that outputs the correct 3D for THAT screenshot. With many screenshots, you may come closer to what you want (AFAI understand your question).<br>
  But remember that without 2 eyes, you have problems with 3D objects. Doesn't mean it's impossible.<br>
  May I suggest you to have a look at convolutional neural networks also <a href="https://en.wikipedia.org/wiki/Convolutional_neural_network" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Convolutional_neural_network</a></p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:06:11.370Z
Answers.Text: So am i correct in saying that if i can get enough visual information of an object (ie enough screenshots of different angles) and encode it into a higher representation (like identifying that theres a face) i can map that encoded information to a mesh of 3d coordinates?
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:18:56.773Z
Answers.Text: If you know the angles (more precisely the position of the...say camera), you don't even have to use a NN. ;)
Answers.UserDisplayName: jcm69
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:21:30.763Z
Answers.Text: if i have a 3d mesh with geometry (lets say 4 square faces, each face containing 4 vertices) is there a way to represent the polygons edges? becuase if i have 4 vertices i still dont know where the edges are
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:40:37.727Z
Answers.Text: Ok, say you have 2 views from 2 cameras (with known position) of a single point (say a light), then you can reconstruct it's position in a 3D space. Easy. Based on that, you can do many things. That's been the case for years. But it's complicated and specialized. While NN have incredible results that classical approaches can't achieve in a quite simple way. Here, *quite* means that you've got to be familiar with NN. Often takes time, really ;)
Answers.UserDisplayName: jcm69
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:42:32.853Z
Answers.Text: ok but how can i represent a 3d mesh in terms of its faces instead of its vertices?
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:42:58.127Z
Answers.Text: if i have a cube, how can i represent each face of the cube instead of the vertices of each corner
Answers.UserDisplayName: Mark Markrowave Charlton
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-14T00:03:44.120Z
Answers.Text: May be by its normal vector ? I'm not a specialist of that domain, really sorry. Sure you'll be interested by http://yann.lecun.com/
Answers.UserDisplayName: jcm69
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-06-13T23:01:46.040Z
Answers.LastActivityDate: 2017-06-13T23:01:46.040Z
Answers.UserDisplayName: jcm69
Body: <p>Is it possible to train a neural network to learn something via video footage (which is essentially a sequence of images)?</p>
  
  <p>In other words, if I have a video teaching me how to draw an animal from scratch, can I then use this video to teach the computer to draw the animal in the same way?</p>
  
  <p>There are many machine learning and image processing techniques (such as RNNs) that can be applied to sequences of images or videos. So, I guess the difficult part becomes mapping the activity to an action like moving a pen or something.</p>
  
Tags: <neural-networks><machine-learning><training><image-processing>
Title: Is it possible to train a neural network to learn something via video footage?
UserDisplayName: Mark Markrowave Charlton
ThreadText: # Is it possible to train a neural network to learn something via video footage?
  
  (Asked by: username_0 on 2017-06-12)
  
  Is it possible to train a neural network to learn something via video footage (which is essentially a sequence of images)?
  
  In other words, if I have a video teaching me how to draw an animal from scratch, can I then use this video to teach the computer to draw the animal in the same way?
  
  There are many machine learning and image processing techniques (such as RNNs) that can be applied to sequences of images or videos. So, I guess the difficult part becomes mapping the activity to an action like moving a pen or something.
  
  **Tags:** neural-networks, machine-learning, training, image-processing
  
  ---
  
  ## 3 answers
  
  ### Answer by username_1 on 2017-06-12. Score: 1
  
  Short answer: No.
  
  Long answer: A neural network is a function that maps input data (e.g. a picture) to output data (e.g. probability that the picture contains a dog). What you propose does not seem like the sort of task this tool is suited for, though I'm not willing to claim that it can't be done.
  
  If you are interested in computer-generated artwork, I encourage you to learn about [Generative Adversarial Networks](http://blog.aylien.com/introduction-generative-adversarial-networks-code-tensorflow/) and [style transfer](https://www.youtube.com/watch?v=Oex0eWoU7AQ).
  
  > **Comments:**
  > **username_0**: You have only described a neural network as a classification tool.. what about reinforcement learning and regression-based nets?  
  > **username_1**: The use case doesn't change the fundamental concept of the net - it's still a function mapping input variables to output variables.  
  > **username_0**: Ok, am i able to map 3d coordinates from a 2d input? lets say i make a 3d object and screenshot it, can i map one to the other?  
  > **username_1**: So a network that maps a 2D representation of an object to its 3D vertices? That sounds feasible.  
  > **username_0**: ok cool im on to it!  
  
  ---
  
  ### Answer by username_2 on 2017-06-13. Score: 1
  
  Just like the other answer - it can't really be done like that. However, you might want to take a look at [Google Deepdream](https://github.com/google/deepdream), which actually enhances images to look more like what they detected. E.g., if a cat is detected, it will make the picture more cat-like.
  
  
  ---
  
  ### Answer by username_3 on 2017-06-13. Score: 0
  
  About the screenshot you mentioned in comments: don't forget that NN build the mappings from learning. With only one screenshot, you'll only be able to construct a NN that outputs the correct 3D for THAT screenshot. With many screenshots, you may come closer to what you want (AFAI understand your question).  
  But remember that without 2 eyes, you have problems with 3D objects. Doesn't mean it's impossible.  
  May I suggest you to have a look at convolutional neural networks also <https://en.wikipedia.org/wiki/Convolutional_neural_network>
  
  > **Comments:**
  > **username_0**: So am i correct in saying that if i can get enough visual information of an object (ie enough screenshots of different angles) and encode it into a higher representation (like identifying that theres a face) i can map that encoded information to a mesh of 3d coordinates?  
  > **username_3**: If you know the angles (more precisely the position of the...say camera), you don't even have to use a NN. ;)  
  > **username_0**: if i have a 3d mesh with geometry (lets say 4 square faces, each face containing 4 vertices) is there a way to represent the polygons edges? becuase if i have 4 vertices i still dont know where the edges are  
  > **username_3**: Ok, say you have 2 views from 2 cameras (with known position) of a single point (say a light), then you can reconstruct it's position in a 3D space. Easy. Based on that, you can do many things. That's been the case for years. But it's complicated and specialized. While NN have incredible results that classical approaches can't achieve in a quite simple way. Here, *quite* means that you've got to be familiar with NN. Often takes time, really ;)  
  > **username_0**: ok but how can i represent a 3d mesh in terms of its faces instead of its vertices?  
  > **username_0**: if i have a cube, how can i represent each face of the cube instead of the vertices of each corner  
  > **username_3**: May be by its normal vector ? I'm not a specialist of that domain, really sorry. Sure you'll be interested by http://yann.lecun.com/  
  
  ---
  
  