text:
\subsection{Datasets}

\paragraph*{TGIF-QA \cite{jang2017tgif}}

This is currently the most prominent dataset for $\Problem$, containing
165K QA pairs and 72K animated GIFs. The dataset covers four tasks
addressing unique properties of video. Of which, the first three
require strong spatio-temporal reasoning abilities\emph{: Repetition
Count} - to retrieve number of occurrences of an action, \emph{Repeating
Action}- multi-choice task to identify the action repeated for a
given number of times, \emph{State Transition} - multi-choice tasks
regarding temporal order of events. The last task - \emph{Frame QA}
- is akin to image QA where a particular frame in a video is sufficient
to answer the questions.\vspace{-4mm}

\paragraph{MSVD-QA \cite{xu2017video}}

This is a small dataset of 50,505 question answer pairs annotated
from 1,970 short clips. Questions are of five types, including what,
who, how, when and where.

\vspace{-4mm}

\paragraph*{MSRVTT-QA \cite{xu2016msr}}

The dataset contains 10K videos and 243K question answer pairs. Similar
to MSVD-QA, questions are of five types. Compared to the other two
datasets, videos in MSRVTT-QA contain more complex scenes. They are
also much longer, ranging from 10 to 30 seconds long, equivalent to
300 to 900 frames per video.

We use accuracy to be the evaluation metric for all experiments, except
those for repetition count on TGIF-QA dataset where Mean Square Error
(MSE) is applied.

\subsection{Implementation Details}

Videos are segmented into 8 clips, each clip contains 16 frames by
default. Long videos in MSRVTT-QA are additionally segmented into
24 clips for evaluating the ability of handling very long sequences.
Unless otherwise stated, the default setting is with a 2-level $\ModelName$
as depicted in Fig.~\ref{fig:Overview-of-Network}, and $d=512$,
$t=1$. We train the model initially at learning rate of $10^{-4}$
and decay by half after every 10 epochs. All experiments are terminated
after 25 epochs and reported results are at the epoch giving the best
validation accuracy. Pytorch implementation of the model is available
online\footnote{https://github.com/thaolmk54/hcrn-videoqa}.

\begin{table}
\begin{centering}
\begin{tabular}{l|c|c|c|c}
\hline
Model & Action & Trans. & Frame & Count\tabularnewline
\hline
ST-TP \cite{jang2017tgif} & 62.9 & 69.4 & 49.5 & 4.32\tabularnewline
Co-mem \cite{gao2018motion} & 68.2 & 74.3 & 51.5 & 4.10\tabularnewline
PSAC \cite{li2019beyond} & 70.4 & 76.9 & 55.7 & 4.27\tabularnewline
HME \cite{fan2019heterogeneous} & 73.9 & 77.8 & 53.8 & 4.02\tabularnewline
\textbf{HCRN} & \textbf{75.0} & \textbf{81.4} & \textbf{55.9} & \textbf{3.82}\tabularnewline
\hline
\end{tabular}\medskip{}
\par\end{centering}
\caption{Comparison with the state-of-the-art methods on TGIF-QA dataset. For
count, the lower the better.\label{tab:tgif}}
\end{table}

\begin{figure}
\begin{centering}
\includegraphics[width=0.8\columnwidth,height=0.63\columnwidth]{figures/msvd_msrvtt_results}\vspace{-2mm}
\par\end{centering}
\caption{Performance comparison on MSVD-QA and MSRVTT-QA dataset with state-of-the-art
methods: Co-mem \cite{gao2018motion}, HME \cite{fan2019heterogeneous},
HRA \cite{chowdhury2018hierarchical}, and AMU \cite{xu2017video}.
\label{fig:msvd-msrvtt}}
\medskip{}
\end{figure}

\subsection{Results}

\subsubsection{Benchmarking against SoTAs}

We compare our proposed model with state-of-the-art methods (SoTAs)
on aforementioned datasets. For TGIF-QA, we compare with most recent
SoTAs, including \cite{fan2019heterogeneous,gao2018motion,jang2017tgif,li2019beyond},
over four tasks. These works, except for \cite{li2019beyond}, make
use of motion features extracted from optical flow or 3D CNNs.

The results are summarized in Table~\ref{tab:tgif} for TGIF-QA,
and in Fig.~\ref{fig:msvd-msrvtt} for MSVD-QA and MSRVTT-QA. Reported
numbers of the competitors are taken from the original papers and
\cite{fan2019heterogeneous}. It is clear that our model consistently
outperforms or is competitive with SoTA models on all tasks across
all datasets. The improvements are particularly noticeable when strong
temporal reasoning is required, i.e., for the questions involving
actions and transitions in TGIF-QA. These results confirm the significance
of considering both near-term and far-term temporal relations toward
finding correct answers.

The MSVD-QA and MSRVTT-QA datasets represent highly challenging benchmarks
for machine compared to the TGIF-QA, thanks to their open-ended nature.
Our model $\ModelName$ outperforms existing methods on both datasets,
achieving 36.1\% and 35.6\% accuracy which are 1.7 points and 0.6
points improvement on MSVD-QA and MSRVTT-QA, respectively. This suggests
that the model can handle both small and large datasets better than
existing methods.

Finally, we provide a justification for the competitive performance
of our $\ModelName$ against existing rivals by comparing model features
in Table~\ref{tab:Model-design-choices}. Whilst it is not straightforward
to compare head-to-head on internal model designs, it is evident that
effective video modeling necessitates handling of motion, temporal
relation and hierarchy at the same time. We will back this hypothesis
by further detailed studies in Section~\ref{subsec:Ablation-Studies}
(for motion, temporal relations, shallow hierarchy) and Section~\ref{subsec:Deepening-model-hierarchy}
(deep hierarchy).

\begin{table}
\begin{centering}
\vspace{-1mm}
{\scriptsize{}}%
\begin{tabular}{l|c|c|c|c}
\hline
{\small{}Model} & {\small{}Appear.} & {\small{}Motion} & {\small{}Hiera.} & {\small{}Relation}\tabularnewline
\hline
{\small{}ST-TP \cite{jang2017tgif}} & {\small{}$\checkmark$} & {\small{}$\checkmark$} &  & \tabularnewline
{\small{}Co-mem \cite{gao2018motion}} & {\small{}$\checkmark$} & {\small{}$\checkmark$} &  & \tabularnewline
{\small{}PSAC \cite{li2019beyond}} & {\small{}$\checkmark$} &  &  & \tabularnewline
{\small{}HME \cite{fan2019heterogeneous}} & {\small{}$\checkmark$} & {\small{}$\checkmark$} &  & \tabularnewline
{\small{}$\ModelName$} & {\small{}$\checkmark$} & {\small{}$\checkmark$} & {\small{}$\checkmark$} & {\small{}$\checkmark$}\tabularnewline
\hline
\end{tabular}\medskip{}
\par\end{centering}
\caption{Model design choices and input modalities in comparison. See Table~\ref{tab:tgif}
for corresponding performance on TGIF-QA dataset. \label{tab:Model-design-choices}}
\medskip{}
\end{table}

\subsubsection{Ablation Studies \label{subsec:Ablation-Studies}}

\begin{table}
\centering{}%
\begin{tabular}{l|c|c|c|c}
\hline
{\small{}Model} & {\small{}Act.} & {\small{}Trans.} & {\small{}F.QA} & {\small{}Count}\tabularnewline
\hline
\hline
\textbf{\small{}Relations $(k_{max},t)$} &  &  &  & \tabularnewline
{\small{}$\quad$$k_{max}=1,t=1$} & {\small{}65.2} & {\small{}75.5} & {\small{}54.9} & {\small{}3.97}\tabularnewline
{\small{}$\quad$$k_{max}=1,t=3$} & {\small{}66.2} & {\small{}76.2} & {\small{}55.7} & {\small{}3.95}\tabularnewline
{\small{}$\quad$$k_{max}=1,t=5$} & {\small{}65.4} & {\small{}76.7} & {\small{}56.0} & {\small{}3.91}\tabularnewline
{\small{}$\quad$$k_{max}=1,t=9$} & {\small{}65.6} & {\small{}75.6} & {\small{}56.3} & {\small{}3.92}\tabularnewline
{\small{}$\quad$$k_{max}=1,t=11$} & {\small{}65.4} & {\small{}75.1} & {\small{}56.3} & {\small{}3.91}\tabularnewline
{\small{}$\quad$$k_{max}=2,t=2$} & {\small{}67.2} & {\small{}76.6} & {\small{}56.7} & {\small{}3.94}\tabularnewline
{\small{}$\quad$$k_{max}=2,t=9$} & {\small{}66.3} & {\small{}76.7} & {\small{}56.5} & {\small{}3.92}\tabularnewline
{\small{}$\quad$$k_{max}=4,t=2$} & {\small{}64.0} & {\small{}75.9} & {\small{}56.2} & {\small{}3.87}\tabularnewline
{\small{}$\quad$$k_{max}=4,t=9$} & {\small{}66.3} & {\small{}75.6} & {\small{}55.8} & {\small{}4.00}\tabularnewline
{\small{}$\quad$$k_{max}=\left\lfloor n/2\right\rfloor ,t=2$} & {\small{}73.3} & {\small{}81.7} & {\small{}56.1} & {\small{}3.89}\tabularnewline
{\small{}$\quad$$k_{max}=\left\lfloor n/2\right\rfloor ,t=9$} & {\small{}72.5} & {\small{}81.1} & {\small{}56.6} & {\small{}3.82}\tabularnewline
{\small{}$\quad$$k_{max}=n-1,t=1$} & {\small{}75.0} & {\small{}81.4} & {\small{}55.9} & {\small{}3.82}\tabularnewline
{\small{}$\quad$$k_{max}=n-1,t=3$} & {\small{}75.1} & {\small{}81.5} & {\small{}55.5} & {\small{}3.91}\tabularnewline
{\small{}$\quad$$k_{max}=n-1,t=5$} & {\small{}73.6} & {\small{}82.0} & {\small{}54.7} & {\small{}3.84}\tabularnewline
{\small{}$\quad$$k_{max}=n-1,t=7$} & {\small{}75.4} & {\small{}81.4} & {\small{}55.6} & {\small{}3.86}\tabularnewline
{\small{}$\quad$$k_{max}=n-1,t=9$} & {\small{}74.1} & {\small{}81.9} & {\small{}54.7} & {\small{}3.87}\tabularnewline
\hline
\textbf{\small{}Hierarchy} &  &  &  & \tabularnewline
{\small{}$\quad$$1$-level, video $\UnitName$ only} & {\small{}66.2} & {\small{}78.4} & {\small{}56.6} & {\small{}3.94}\tabularnewline
{\small{}$\quad$$1.5$-level, clips$\rightarrow$pool} & {\small{}70.4} & {\small{}80.5} & {\small{}56.6} & {\small{}3.94}\tabularnewline
\hline
\textbf{\small{}Motion conditioning} &  &  &  & \tabularnewline
{\small{}$\quad$w/o motion} & {\small{}70.8} & {\small{}79.8} & {\small{}56.4} & {\small{}4.38}\tabularnewline
{\small{}$\quad$w/o short-term motion} & {\small{}74.9} & {\small{}82.1} & {\small{}56.5} & {\small{}4.03}\tabularnewline
{\small{}$\quad$w/o long-term motion} & {\small{}75.1} & {\small{}81.3} & {\small{}56.7} & {\small{}3.92}\tabularnewline
\hline
\textbf{\small{}Linguistic conditioning} &  &  &  & \tabularnewline
{\small{}$\quad$w/o linguistic condition} & {\small{}66.5} & {\small{}75.7} & {\small{}56.2} & {\small{}3.97}\tabularnewline
{\small{}$\quad$w/o quest.@clip level} & {\small{}74.3} & {\small{}81.1} & {\small{}55.8} & {\small{}3.95}\tabularnewline
{\small{}$\quad$w/o quest.@video level} & {\small{}74.0} & {\small{}80.5} & {\small{}55.9} & {\small{}3.92}\tabularnewline
\hline
\textbf{\small{}Gating} &  &  &  & \tabularnewline
{\small{}$\quad$w/o gate} & {\small{}74.1} & {\small{}82.0} & {\small{}55.8} & {\small{}3.93}\tabularnewline
{\small{}$\quad$w/ gate quest. \& motion} & {\small{}73.3} & {\small{}80.9} & {\small{}55.3} & {\small{}3.90}\tabularnewline
\hline
{\small{}$\quad$Full $2$-level $\ModelName$} & {\small{}75.1} & {\small{}81.2} & {\small{}55.7} & {\small{}3.88}\tabularnewline
\hline
\end{tabular}\medskip{}
\caption{Ablation studies on TGIF-QA dataset. For count, the lower the better.
Act.: Action; Trans.: Transition; F.QA: Frame QA. When not explicitly
specified, we use $k_{max}=n-1,t=2$ for relation order and sampling
resolution. \label{tab:Ablation-tgif}}
\medskip{}
\end{table}

To provide more insight about our model, we conduct extensive ablation
studies on TGIF-QA with a wide range of configurations.\emph{ }The
results are reported in Table~\ref{tab:Ablation-tgif}. \emph{Full
$2$-level $\ModelName$} denotes the full model of Fig.~\ref{fig:Overview-of-Network}
with $k_{max}=n-1,t=2$. Overall we find that ablating any of design
components or $\UnitName$ units would degrade the performance for
temporal reasoning tasks (actions, transition and action counting).
The effects are detailed as follows.\vspace{-3mm}

\paragraph{Effect of relation order $k_{max}$ and resolution $t$}

Without relations ($k_{max}=1$) the performance drops significantly
on actions and events reasoning. This is expected since those questions
often require putting actions and events in relation with a larger
context (e.g., what happens before something else). In this case,
the frame QA benefits more from increasing sampling resolution $t$
because of better chance to find a relevant frame. However, when taking
relations into account ($k_{max}>1$), we find that $\ModelName$
is robust against sampling resolution $t$ but depends critically
on the maximium relation order $k_{max}$. The relative independence
w.r.t. $t$ can be due to visual redundancy between frames, so that
resampling may capture almost the same information. On the other hand,
when considering only low-order object relations, the performance
is significantly dropped in all tasks, except frame QA. These results
confirm that high-order relations are required for temporal reasoning.
As the frame QA task requires only reasoning on a single frame, incorporating
temporal information might confuse the model.\vspace{-5mm}

\paragraph{Effect of hierarchy}

We design two simpler models with only one $\UnitName$ layer: \emph{$\blacktriangleright$
}$1$\emph{-level, $1$ $\UnitName$ video on key frames only}: Using
only one $\UnitName$ at the video-level whose input array consists
of key frames of the clips. Note that video-level motion features
are still maintained. \emph{$\blacktriangleright$ }$1.5$-\emph{level,
clip $\UnitName$s $\rightarrow$} \emph{pooling}: Only the clip-level
$\UnitName$s are used, and their outputs are mean-pooled to represent
video. The pooling operation represents a simplistic relational operation
across clips. The results confirm that a hierarchy is needed for high
performance on temporal reasoning tasks.\vspace{-3mm}

\paragraph{Effect of motion conditioning}

We evaluate the following settings: \emph{$\blacktriangleright$ w/o
short-term motions}: Remove all $\UnitName$ units that condition
on the short-term motion features (clip level) in the $\ModelName$.
\emph{$\blacktriangleright$ w/o long-term motions}: Remove the $\UnitName$
unit that conditions on the long-term motion features (video level)
in the $\ModelName$.\emph{ $\blacktriangleright$ w/o motions}: Remove
motion feature from being used by $\ModelName$. We find that motion,
in agreeing with prior arts, is critical to detect actions, hence
computing action count. Long-term motion is particularly significant
for counting task, as this task requires maintaining global temporal
context during the entire process. For other tasks, short-term motion
is usually sufficient. E.g. in action task, wherein one action is
repeatedly performed during the entire video, long-term context contributes
little. Not surprisingly, motion does not play the positive role in
answering questions on single frames as only appearance information
needed.\vspace{-3mm}

\paragraph{Effect of linguistic conditioning and gating}

Linguistic cues represent a crucial context for selecting relevant
visual artifacts. For that we test the following ablations:\emph{
$\blacktriangleright$ w/o quest.@clip level}: Remove the $\UnitName$
unit that conditions on question representation at clip level. \emph{$\blacktriangleright$
w/o quest.@video level}: Remove the $\UnitName$ unit that conditions
on question representation at video level. \emph{$\blacktriangleright$
w/o linguistic condition: }Exclude all $\UnitName$ units conditioning
on linguistic cue while the linguistic cue is still in the answer
decoder. Likewise, gating offers a selection mechanism. Thus we study
its effect as follows: \emph{$\blacktriangleright$ wo/ gate}: Turn
off the self-gating mechanism in all $\UnitName$ units.\emph{ $\blacktriangleright$
w/ gate quest. \& motion}: Turn on the self-gating mechanism in all
$\UnitName$ units.

We find that the conditioning question provides an important context
for encoding video. Conditioning features (motion and language), through
the gating mechanism in Eq.~(\ref{eq:gating_h}), offers further
performance gain in action and counting tasks, possibly by selectively
passing question-relevant information up the inference chain.

\begin{table}
\begin{centering}
\begin{tabular}{l|c}
\hline
Depth of hierarchy & Overall Acc.\tabularnewline
\hline
$2$-level, $24$ clips $\rightarrow$ $1$ vid & 35.6\tabularnewline
$3$-level, $24$ clips $\rightarrow$ $4$ sub-vids $\rightarrow$
$1$ vid & 35.6\tabularnewline
\hline
\end{tabular}\medskip{}
\par\end{centering}
\caption{Results for going deeper hierarchy on MSRVTT-QA dataset. Run time
is reduced by factor of $4$ for going from 2-level to 3-level hierarchy.
\label{tab:scale_analysis-msrvtt}}
\medskip{}
\end{table}

\subsubsection{Deepening model hierarchy \label{subsec:Deepening-model-hierarchy}}

We test the scalability of the HCRN on long videos in the MSRVTT-QA
dataset, which are organized into 24 clips (3 times longer than other
two datasets). We consider two settings: \emph{$\blacktriangleright$
$2$-level hierarchy,} \emph{$24$ clips}$\rightarrow$$1$ \emph{vid}:
The model is as illustrated in Fig.~\ref{fig:Overview-of-Network},
where 24 clip-level $\UnitName$s are followed by a video-level $\UnitName$.
\emph{$\blacktriangleright$ $3$-level hierarchy}, $24$ \emph{clips}$\rightarrow$$4$\emph{
sub-vid}s$\rightarrow$$1$ \emph{vid}: Starting from the 24 clips
as in the $2$-level hierarchy, we group 24 clips into 4 sub-videos,
each is a group of 6 consecutive clips, resulting in a $3$-level
hierarchy. These two models are designed to have similar number of
parameters, approx. 50M.

The results are reported in Table~\ref{tab:scale_analysis-msrvtt}.
Unlike existing methods which usually struggle with handling long
videos, our method is scalable for them by offering deeper hierarchy,
as analyzed theoretically in Section~\ref{subsec:Complexity-Analysis}.
Using a deeper hierarchy is expected to significantly reduce the training
time and inference time for $\ModelName$, especially when the video
is long. In our experiments, we achieve \emph{4 times reduction in
training and inference time} by going from 2-level $\ModelName$ to
3-level counterpart whilst maintaining the same performance.

\section{Introduction}

\input{intro.tex}

\section{Related Work \label{sec:Related-Work}}

\input{related.tex}

\section{Method \label{sec:Method}}

\input{method_post_review.tex}

\section{Experiments \label{sec:Experiments}}

\input{exps.tex}

\section{Discussion \label{sec:Discussion}}

\input{discussion.tex}

{\small{}\bibliographystyle{ieee}

\subsection{Conditional Relation Network Unit\label{subsec:Multiscale-Relation-Network}}

We introduce a reusable computation unit, termed Conditional Relation
Network ($\UnitName$), which takes as input an array of $n$ objects
$\mathcal{S}=\{s_{i}\}_{i=1}^{n}$ and a conditioning feature $c$
- both in the same vector space $\mathbb{R}^{d}$ or tensor space
$\mathbb{R}^{W\times H\times d}$. CRN generates an output array of
objects of the same dimensions containing high-order object relations
of input features given the global context. The operation of CRN unit
is presented algorithmically in Alg.~\ref{algo:CRN} and visually
in Fig.~\ref{fig:Illustration-of-Multiscales}. Table \ref{tab:notations}
summarizes the notations used across these presentations.

When in use for $\Problem$, CRN's input array is composed of features
at either frame or short-clip levels. The objects $\{s_{i}\}_{i=1}^{n}$
greatly share mutual information and it is redundant to consider all
possible combinations of given objects. Therefore, applying a sampling
scheme on the set of subsets (line 4 of Alg.~\ref{algo:CRN}) is
crucial for redundancy reduction and computational efficiency. We
borrow the sampling trick in \cite{zhou2018temporal} to build sets
of $t$ selected subsets $Q_{\textrm{selected}}^{k}$. Regarding the
choice of $k_{\text{max}}$, we choose $k_{\text{max}}=n-1$ in later
experiments, resulting in the output array of size $n-2$ if $n>2$
and array of size $1$ if $n=2$.

As a choice in implementation, the functions $g^{k}(.),p^{k}(.)$
are simple average-pooling. In generic form, they can be any aggregation
sub-networks that join a random set into a single representation.
Meanwhile, $h^{k}(.,.)$ is a MLP running on top of feature concatenation
that models the non-linear relationships between multiple input modalities.
We tie parameters of the conditioning sub-network $h^{k}(.,.)$ across
the subsets of the same size $k$. In our implementation, $h^{k}(.,.)$
consists of a single linear transformation followed by an ELU \cite{clevert2015fast}
activation.

It may be of concern that the relation formed by a particular subset
may be unnecessary to model $k$-tuple relations, we optionally design
a self-gating mechanism similar to \cite{dauphin2017language} to
regulate the feature flow to go through each $\UnitName$ module.
Formally, the conditioning function $h^{k}(.,.)$ in that case is
given by:\vspace{-5mm}

\begin{equation}
h^{k}\left(x,y\right)=\text{ELU(}W_{h_{1}}\left[x,y\right])*\sigma\left(W_{h_{2}}\left[x,y\right]\right),\label{eq:gating_h}
\end{equation}
where $[.,.]$ denotes the tensor concatenation, $\sigma$ is sigmoid
function, and $W_{h_{1}},W_{h_{2}}$ are linear weights.

\subsection{Hierarchical Conditional Relation Networks \label{subsec:HCRN}}

We use $\UnitName$ blocks to build a deep network architecture to
exploit inherent characteristics of a video sequence namely temporal
relations, motion, and the hierarchy of video structure, and to support
reasoning guided by linguistic questions. We term the proposed network
architecture Hierarchical Conditional Relation Networks ($\ModelName$)
(see Fig.~\ref{fig:Overview-of-Network} ). The design of the $\ModelName$
by stacking reusable core units is partly inspired by modern CNN network
architectures, of which InceptionNet \cite{szegedy2015going} and
ResNet \cite{he2016deep} are the most well-known examples.

A model for $\Problem$ should distill the visual content in the context
of the question, given the fact that much of the visual information
is usually not relevant to the question. Drawing inspiration from
the hierarchy of video structure, we boil down the problem of $\Problem$
into a process of video representation in which a given video is encoded
progressively at different granularities, including short clip (consecutive
frames) and entire video levels. It is crucial that the whole process
conditions on linguistic cue. In particular, at each hierarchy level,
we use two stacked $\UnitName$ units, one conditioned on motion features
followed by one conditioned on linguistic cues. Intuitively, the motion
feature serves as a dynamic context shaping the temporal relations
found among frames (at the clip level) or clips (at the video level).
As the shaping effect is applied to all relations, self-gating is
not needed, and thus a simple MLP suffices. On the other hand, the
linguistic cues are by nature selective, that is, not all relations
are equally relevant to the question. Thus we utilize the self-gating
mechanism in Eq.~(\ref{eq:gating_h}) for the $\UnitName$ units
which condition on question representation.

With this particular design of network architecture, the input array
at clip level consists of frame-wise appearance feature vectors $\{\hat{v}_{ij}\}$,
while that at a video level is the output at the clip level. Meanwhile,
the motion conditioning feature at clip level CRNs are corresponding
clip motion feature vector $\hat{f}_{i}$. They are further passed
to an LSTM, whose final state is used as video-level motion features.
Note that this particular implementation is not the only option. We
believe we are the first to progressively incorporate multiple modalities
of input in such a hierarchical manner in contrast to the typical
approach of treating appearance features and motion features as a
two-stream network.

To handle a long video of thousand frames, which is equivalent to
dozens of short-term clips, there are two options to reduce the computational
cost of $\UnitName$ in handling large sets of subsets $\{Q^{k}|k=2,3,...,k_{\text{max}}\}$
given an input array $S$: limit the maximum subset size $k_{\text{max}}$
or extend the $\ModelName$ to deeper hierarchy. For the former option,
this choice of sparse sampling may have potential to lose critical
relation information of specific subsets. The latter, on the other
hand, is able to densely sample subsets for relation modeling. Specifically,
we can group $N$ short-term clips into $N_{1}\times N_{2}$ hyper-clips,
of which $N_{1}$ is the number of the hyper-clips and $N_{2}$ is
the number of short-term clips in one hyper-clip. By doing this, our
$\ModelName$ now becomes a 3-level of hierarchical network architecture.

At the end of the $\ModelName$, we compute the average visual feature
based on conditioning to the question representation $q$. Assume
outputs of the last $\UnitName$ unit at video level are an array
$O=\left\{ o_{i}\mid o_{i}\in\mathbb{R}^{H\times d}\right\} _{i=1}^{N-4}$,
we first stack them together, resulting in an output tensor $o\in\mathbb{R}^{(N-4)\times H\times d}$,
and further vectorize this output tensor to obtain the final output
$o^{\prime}\in\mathbb{R}^{H^{\prime}\times d},H^{\prime}=(N-4)\times H$.
The weighted average information is given by:

\vspace{-3mm}

\begin{align}
I & =\left[W_{o^{\prime}}o^{\prime},W_{o^{\prime}}o^{\prime}\odot W_{q}q\right],\\
I^{\prime} & =\text{ELU}\left(W_{I}I+b\right),\\
\gamma & =\text{softmax}\left(W_{I^{\prime}}I^{\prime}+b\right),\\
\tilde{o} & =\sum_{h=1}^{H^{\prime}}\gamma_{h}o_{h}^{\prime};\,\tilde{o}\in\mathbb{R}^{d},
\end{align}
where, $\left[.,.\right]$ denotes concatenation operation, and $\odot$
is the Hadamard product.

\subsection{Answer Decoders and Loss Functions\label{subsec:Answer-Decoders}}

Following \cite{jang2017tgif,song2018explore,fan2019heterogeneous},
we adopt different answer decoders depending on the task. Open-ended
questions are treated as multi-label classification problems. For
these, we employ a classifier which takes as input the combination
of the retrieved information from visual cue $\tilde{o}$ and the
question representation $q$, and computes label probabilities $p\in\mathbb{R}^{|\mathcal{A}|}$:\vspace{-1.3mm}

\begin{align}
y & =\text{ELU}\left(W_{o}\left[\tilde{o},W_{q}q+b\right]+b\right),\\
y^{\prime} & =\text{ELU}\left(W_{y}y+b\right),\label{eq:9}\\
p & =\textrm{softmax}\left(W_{y^{\prime}}y^{\prime}+b\right).
\end{align}
The cross-entropy is used as the loss function.

For repetition count task, we use a linear regression function taking
$y^{\prime}$ in Eq.~(\ref{eq:9}) as input, followed by a rounding
function for integer count results. The loss for this task is Mean
Squared Error (MSE).

For multi-choice question types (such as repeating action and state
transition in TGIF-QA), each answer candidate is processed in the
same way with the question. In detail, we use the shared parameter
$\ModelName$s with either question or each answer candidate as language
cues. As a result, we have a set of $\ModelName$ outputs, one conditioned
on question ($\tilde{o}_{q}$), and the others conditioned on answer
candidates ($\tilde{o}_{a})$. Subsequently, $\tilde{o}_{q},$ $\{\tilde{o}_{a}\}$,
question representation $q$ and answer candidates $a$ are fed into
a final classifier with a linear regression to output an answer index,
as follows:\vspace{-1.3mm}
\begin{align}
y & =\left[\tilde{o}_{q},\tilde{o}_{a},W_{q}q+b,W_{a}a+b\right],\\
y^{\prime} & =\text{ELU}\left(W_{y}y+b\right),\\
s & =W_{y^{\prime}}y^{\prime}+b.
\end{align}
We use the popular hinge loss \cite{jang2017tgif} of pairwise comparisons,
$\text{max}\left(0,1+s^{n}-s^{p}\right)$, between scores for incorrect
$s^{n}$ and correct answers $s^{p}$ to train the network.

\subsection{Complexity Analysis \label{subsec:Complexity-Analysis}}

We provide a brief analysis here, leaving detailed derivations in
Supplement. For a fixed sampling resolution $t$, a single forward
pass of $\UnitName$ would take quadratic time in $k_{\text{max}}$.
For an input array of length $n$, feature size $F$, the unit produces
an output array of size $k_{\text{max}}-1$ of the same feature dimensions.
The overall complexity of $\ModelName$ depends on design choice for
each $\UnitName$ unit and specific arrangement of $\UnitName$ units.
For clarity, let $t=2$ and $k_{\max}=n-1$, which are found to work
well in later experiments. Suppose there are $N$ clips of length
$T$, making a video of length $L=NT$. A 2-level architecture of
Fig.~\ref{fig:Overview-of-Network} needs $2TLF$ time to compute
the $\UnitName$s at the lowest level, and $2NLF$ time to compute
the second level, totaling $2(T+N)LF$ time.

Let us now analyze a 3-level architecture that generalizes the one
in Fig.~\ref{fig:Overview-of-Network}. The $N$ clips are organized
into $M$ sub-videos, each has $Q$ clips, i.e., $N=MQ$. The clip-level
$\UnitName$s remain the same. At the next level, each sub-video $\UnitName$
takes as input an array of length $Q$, whose elements have size $(T-4)F$.
Using the same logic as before, the set of sub-video-level CRNs cost
$2\frac{N}{M}LF$ time. A stack of two sub-video $\UnitName$s now
produces an output array of size $(Q-4)(T-4)F$, serving as an input
object in an array of length $M$ for the video-level $\UnitName$s.
Thus the video-level $\UnitName$s cost $2MLF$. Thus the total cost
for 3-level $\ModelName$ is in the order of $2(T+\frac{N}{M}+M)LF$.

Compared to the 2-level $\ModelName$, the a 3-level $\ModelName$
reduces computation time by $2(N-\frac{N}{M}-M)LF\approx2NLF$ assuming
$N\gg\max\left\{ M,\frac{N}{M}\right\} $. As $N=\frac{L}{T}$, this
reduces to $2NLF=2\frac{L^{2}}{T}F$. In practice $T$ is often fixed,
thus the saving scales quadratically with video length $L$, suggesting
that hierarchy is computational efficient for long videos.

redpajama_set_name: RedPajamaArXiv


I know exactly how you feel. I spent a year in LA accumulating massive amounts of debt before finally getting a job - and it was blind luck that finally I even got it in the first place. And now I'm unemployed and once again in a desperate search for work (although this time I at least have some money saved up and I qualify for unemployment) But still that feeling of being utterly useless, I hate it almost more then the lack of income.
Many hugs to you too!!
If someone with your talents, experience, and overall awesomeness can't get a job, I may end up in a looney bin. I really hope you can land a job before your resources run out.
Sigh. I REALLY hate money.
Your Stephen Fry icon makes me smile.
Not everything is crap. I still have my friends :) So far. I wouldn't blame them if they left me behind. And my mom hasn't literally kicked me out... yet. She just makes my every breath in her house a huge guilt trip.
I'm apparently not good enough at what I do, which is what I've always feared was true.
Ha, my mom had been joking that she's going to send me to England, because I could become a citizen and at least get more benefits there then here in America. Pretty pathetic! I'm so worried about getting stuck in my situation with no way of getting out. If I get stuck, everything I've done up to this point has been a complete waste.
There's only one thing for it - me, you, civil partnership, benefits! It's s oeasy to get benefits here, it's kind of pathetic.
I hope the Angel can bring a job for me. Maybe the Angel needs someone to clean its wings, wash its robe, make its coffee... be its pet. I'm willing to wear a leash and crawl on all fours.
Thank you, Terri. Love you too, as always.


text:
Nordica Photography
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Glasgow Wedding Photography
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And we want to keep doing that. We want to photograph weddings all around the world. Including Glasgow.
Destination Wedding Glasgow
So that's us. Let's move over to you. We really want to hear from you. We want to see if we're potentially a fit to photograph your wedding, which is why we set up a short form below. If you fill out the fields and provide us with a bit of information, we'll get back to you right away (usually within 24 hours) and see if there is potential there for us to photograph your wedding in Glasgow.
Cole & Jakob
Let's share some information and learn more about your story.
Your Names(required)
Date of Wedding or Session
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Town, city, country - just a general idea where you're thinking of doing this.
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text:
SYS Podcast Episode 316: With Writer/Director Martin Gooch (transcript)
This is a transcript of SYS Podcast Episode 316: With Writer/Director Martin Gooch.
Ashley: Welcome to Episode #316 of the Selling Your Screenplay podcast. I'm Ashley Scott Meyers, screenwriter and blogger over at www.sellingyourscreenplay.com. Today I'm interviewing director Martin Gooch about his new movie Atomic Apocalypse. It's a low budget Sci-fi action film, it looks fantastic. Martin has been on the podcast previously too, so check out those episodes if you wanna learn a little bit more about him and his background. He was on in Episode #17 and also on in Episode #204. So check those out if you haven't already listened to them, I will link to those in the show notes, but in the meantime, stay tuned for the interview with Martin on his new movie Atomic Apocalypse.
If you find this episode valuable, please help me out by giving me a review on iTunes or leaving a comment on YouTube or retweeting the podcast on Twitter or liking or sharing it on Facebook. These social media shares really do help spread word about the podcast, so they're very much appreciated. Any websites or links that I mention in the podcast can be found on my blog in the show notes. I also publish a transcript with every episode in case you'd rather read the show or look at something later on. You can find all the podcast show notes at www.sellingyourscreenplay.com/podcast and then just look for Episode Number #316. If you want my free guide-How To Sell a Screenplay in Five Weeks, you can pick that up by going to www.sellingyourscreenplay.com/guide.
It's completely free, you just put in your email address and I'll send you a new lesson once per week for five weeks along with a bunch of bonus lessons. I teach the whole process of how to sell your screenplay in that guide. I'll teach you how to write a professional logline and query letter and how to find agents, managers and producers who are looking for material. Really, it's everything you need to know to sell your screenplay. Just go to www.sellingyourscreenplay.com/guide.
Quick few words about what I'm working on. I've got everything ready to launch the Kickstarter campaign on Monday for my horror thriller film called The Rideshare Killer. But if you're listening to this on the day that it's published, which is gonna be Monday, February 17th, it means that that is actually the last day of the Kickstarter campaign. So if you haven't checked it out, please do go check it out now as today, Monday, February 17th will be the last day 2020 Monday, February 17th. So as I record this podcast two weeks before it publishes, I have no idea how it's going. Hopefully the Kickstarter campaign is going well.
Just to give a quick recap if you've missed the last few episodes, I shot a mystery thriller film in December called The Rideshare Killer, starring Eric Roberts and Tuesday Knight and now we've got to raise some money for the postproduction through Kickstarter. I've got the domain name set up, so check that link out, it is www.theridesharekiller.com. That will take you directly to the Kickstarter page if the Kickstarter campaign is still going on, or if you're listening to this after the Kickstarter campaign has ended, it will take you to the official website for the film. So either way you'll be able to learn more about the film if you go to www.theridesharekiller.com. I used a lot of the footage from the Kickstarter video.
That's one of the advantages to shooting the film before doing the Kickstarter campaign. So I was able to use a lot of stills and also just a lot of the actual footage. At the end of the Kickstarter video there's actually a nice little teaser trailer, just a little 15, 20-second scene that I cut together quickly just with the actual footage so you can kinda get a feel for what the movie's actually gonna look and sound like. Any help you can give is greatly appreciated. It doesn't have to be monetary help either. If you're not in a position to contribute, no worries at all. But perhaps just pass the link around to your horror fan friends. Aside from raising money, the whole point of the Kickstarter campaign is to raise awareness for the film.
So anyone that you can mention the film to is a big help and it's greatly appreciated. Anyway, wish us luck. As I said, the campaign is ending today but I'm recording this more than two weeks out so I have no idea if it's doing well. Hopefully it is. Again, the URL if you wanna check it out is www.theridesharekiller.com. Again, that is www.theridesharekiller.com. Needless to say, that's the main thing I have been working on over the last couple of weeks.
So now let's get into the main segment. Today I am interviewing writer- director Martin Gooch. Here is the interview.
Ashley: Welcome back Martin to the Selling Your Screenplay podcast. I really appreciate you coming on the show with me today.
Martin: Oh, it's fantastic to be here for the third time. This is the hat trick.
Ashley: It is. It is. So you've been here, as you mentioned twice before. You were one of my first guests on Episode Number #17, and then you were also on again on Episode #204. I will link to those in the show notes. In Episode Number #17, we kinda went through your origin story, your early career, how you got into the business, so I would definitely refer people back to that episode if they wanna kinda learn more about your background. And then specifically in Episode #204, we talked about your film, The Gatehouse. Again, interesting interview, so I would encourage people to listen to those if they think you have a lot of interesting comments here today. So today we're talking about your film Atomic Apocalypse.
On IMDb I noticed it was labelled as Black Flowers. Is there a title change coming?
Martin: Yeah, when we made it was called Black Flowers. And when I wrote it, it was actually called The Big Oops.
Ashley: Okay [laughs].
Martin: So it started as the Big Oops and then it became Black Flowers. We shot it Black Flowers, we went on the festival route as Black Flowers and we've won a load of awards, which is great. And all the awards have Black Flowers written on them. But we're gonna distribute it, it's gonna come out and it'll be called Atomic Apocalypse.
Ashley: Okay. And was that something the distributor thought Atomic Apocalypse would have more sales value? What was the thought process behind that title change?
Martin: Yeah, exactly that. I mean it's the classic thing. The Atomic Apocalypse is much more immediate. Like if you see that on the poster, you know what the film is about and Black Flowers was, I think I was probably trying to be clever and take that film to a higher level.
Ashley: More impressionistic, yeah. As opposed to on the nose. I got you. Okay. So to start out, maybe you can us a little bit about this film. Do you have a pitch or a log line for it?
Martin: Yeah, in post-apocalyptic North America, one family fights for survival in a world gone to hell.
Ashley: Gotcha. So where did this idea come from? What was the genesis of the story?
Martin: Well, a couple of years ago I was very lucky. I was asked to be a judge at the Santa Barbara Film Festival, I think it was January, 2017. When I was there… it's right on the coast, so it's right by the ocean up in Santa Barbara. When I was there, there was a huge storm. It was the biggest storm California have had for 20 years. I was in the hotel and I had a balcony. I was looking out watching all this lightning coming down like it was the end of the world. It was an apocalyptic moment. I woke up in the morning and all the Palm trees were knocked down, there was a hole in the road and I walked down to the beach and the beach was just covered in flotsam and jetsam and it was really apocalyptic. I walked along and there was this poor dead seal that had been bashed around on the rocks. And I thought, "Oh, this is fantastic." And I took a…
Ashley: Poor seal.
Martin: Yeah. Poor, sorry seal, but good idea. I sat down on a rock and I got my note pad out and I started writing the story. I thought that the interesting thing about the end of days, the apocalypse and everything is even if we as a race of humans nuke ourselves to bits nature will find a way as like in Jurassic Park, nature will find a way. And what's always interesting in all of these war films and post-apocalyptic thing is what happens to the regular man in the street or woman, what happens to the regular ordinary people. Marvel are out there making incredible superhero films and Star Wars are doing fantastic Sci-Fi films. We can't copy that. We haven't the money, we don't have the resources, we don't have the advertising, we don't have the time.
But what we can do is make a tight story about one family of ordinary people and how surviving an apocalypse affects them. That was the genesis of the story.
Ashley: I got you. Perfect. So let's talk about your writing process a little bit, and specifically to this Atomic Apocalypse script. How much did you spend outlining? So you've got your… you're out there with your notepad, it's pouring down rain, you have this sort of the genesis idea. How much did you write right then, and then what does that look like leading up to actually opening final draft and typing out pages?
Martin: I was just wondering if I had it on my desk, but that's another script. I fill up notepads constantly. My desk, if you could see this, it's like got 10 notepads on it, each one for a different project. And then I write lots and lots of notes in…
Ashley: …and that will go on for a couple months or a couple of weeks?
Martin: No, no, just a couple of days. I'll just get it out and then I'll probably open up a Word document and then I'll just brain dump it down. You know, like… because Black Flowers when I wrote it, I wanted to do something that was outside. So my notes would be as simple as exterior trees, forest, coast. Because the great thing about filming outside, if it isn't too cold or isn't raining, you can put the camera anywhere. As soon as you're filming inside a submarine or a kitchen or someone's bathroom, suddenly it gets smaller and smaller and you can't shoot it like a Hollywood film because you can't put the camera where you want it. Because in Hollywood of course they will make a set and they'll take the wall out and you can put the camera wherever you want.
So from a purely practical point of view, filming outside is much easier I think personally. Obviously you have to do it where there isn't a motorway or freeways you can hear. I sort of… I was just thinking of locations I'd like to film at and many, many years ago when I was only 19, I was lucky enough to get a job with the US Forest Service. I was an archeological assistant up in Modoc Forest in North California, which is almost up in Oregon territory. It's right by Mount Shasta. I completely fell in love with the environment there. It's so beautiful, and it's… I was only 19, I'd never been anywhere. I hadn't even been to Paris, and I suddenly was in this huge epic environment with a desert to one direction and mountains with snow on in another and a forest that way and the ocean that way. It was just spectacular.
I loved it and I thought, "I really wanna come back." So I wrote… the film was set in that location. And then when I was at Santa Barbara Film Festival, I met these great filmmakers from Montana and they said, "You've got to come to Montana. It's really beautiful." I said, "I've got this idea for a post-apocalyptic film." And they said, "Hey wow, these guys we know, they own their own bunker from like 1997, the Y2K when they built all these bunkers, they thought the world was gonna end." And I was like, "That sounds cool." They said, "Why don't you come up to Montana and check it out?" And I thought, "Okay, heck yeah!" So I have a friend called Krista DeMille, who's an actress in New York, and we'd been working on a project for a number of years, I think five years at that point, which hadn't come to fruition.
I phoned her up and I said, "Hey look, do you wanna come to Shasta, look at some locations, go up to Montana, check out some locations, see if we can find a way to make a movie and we'll finish writing the script whilst we're up there?" And she said yes. So I carried on writing the script. Basically I was writing it in bullet points and story blocks. So I would say, this happens and this happens and this happens. I think that's the quickest way to write a script. I've written 21 movies, so I've written a lot of movies and you sort of worry about dialogue later and get the story right, get the story right, get the story right, the journey. And then we flew off to Shasta, we saw a huge number of locations, I've forgotten how many, at least, I don't know, let's say 30. And then we went over to…
Ashley: …all different bunkers or just different types of them. Just some bunkers, some…
Martin: Waterfalls, crevasses, tunnels. extinct volcanoes, fields, lakes, ruined petrol stations, gas stations, empty shops, burned-up houses, everything. And then we went across to Montana and then we went to the bunker in Montana. But we only saw two bunkers in Montana because the first bunker we went to was just spectacular. It was like once you've found it, you don't need to carry on looking. If it fits your vision, stop, because that's something you've done. Tick that box and spend your time more constructively.
Ashley: Yeah, sure. It sounds like there's a number of things, you were in love with the location and you had this idea, but it sounds like you've got a bunch of notepads sitting on your desk. Why did you decide to pursue this idea versus any number of these other notepads that are sitting on your desk or are you just always pursuing multiple projects and for some reason this one got funded ahead of some of the other ones? Like this other project that you said you were working on with this actress for the last five years, it didn't get any things like why not push in that direction instead of starting a new project?
Martin: It's a good question. Like most filmmakers, you have many, many projects or plates spinning and the last one or the first one that doesn't crash to the ground, that's the one you go with. I have several projects which I would love to make, one project I've been working on for 35 years. So I'm very keen to make that one day, 35 years. And I've got another project that I've been working on for 25 years. And so I'm very, very…
Ashley: Really?
Martin: Really, really. So I'm very keen for those to go.
Ashley: What's the hurdle? Are they just too big budget you just can't quite get the things you need cast, you can't quite get the right cast in place?
Martin: Yeah. I can't get the money yet, but I will, but it just takes a long time. And what happened was I'd set up a company to raise money and we were raising money and we'd raised a certain amount of money and then unfortunately the UK government decided to change the tax laws and the way we were raising the money, which was all legal and perfectly legit and everything was fine, suddenly it was stopped and there was no… we weren't allowed to raise any more money. And I went and I had this awful meeting where I had to go and I sat in a room with the lawyers and the accountants and me and they said… and I'd raised all this money and it was in a bank account and it was ready to make a movie, but it wasn't enough to make the movie we wanted to make.
And the lawyer said, "You have to give it back." I said, "But I can't give it back because you have already had some of it. So I would have to go and earn your money that you've had, put that into the pot and then give it back to the investors." And the lawyers have had their money and everyone's had their money and I haven't had any money, but they had all their money of course, because lawyers always get their money. They said, "Yeah, yeah, you'd have to do that." And I was like, "Oh my God." I thought I was gonna jump in front of a bridge, in front of a train or jump off a bridge. I mean I could jump in front of a bridge, but that's pointless because the bridge would just stay there, wouldn't it? Ha ha.
It was like the worst day ever. Because I had all this money in the bank and I had to give it back, but I hadn't got enough because we'd already spent it on the lawyers. So I went away and I scratched my head and I thought and I had all these phone calls with the lawyers. It lasted for about maybe a month, we're trying to work out what to do and all these legal stuff going on and more bills. Then I just phoned them up and I said, "Hey guys, can I use the money to make another film?" And they said, "Oh yeah, yeah, you can do that. That's fine." I was like, "God couldn't you have just told me that?"
Ashley: But they weren't gonna get the tax incentives. Wasn't that the crux of this?
Martin: No. The crux was there was no more tax incentive, so anyone else who gave, we could have…
Ashley: Okay. But they made it in under the deadline. I got you. Well, why didn't it occur to the lawyers to do that? Just go to the investors and say, "Can we switch it to this other movie because the tax incentives have changed?"
Martin: I probably just wasn't paying them enough. And had I have given them more money then they would come up with that idea. Because in the end I had to pay them for me to have an idea. So there you go, hooray for lawyers, aren't they great?
Ashley: But the bottom line was you we're able to use that money for Atomic Apocalypse.
Martin: Yeah. I had to go through a stressful little time and talk to all my investors and make sure they were happy with it and all this stuff. Because the thing about making movies is we love being on set and we love writing scripts and we love working with actors and DPs and grips and all those wonderful people and editors. But the truth is, unless you are willing to roll up your sleeves and learn business and money and finance, you're never gonna get to make your movies. Because that is the fundamental building block. That's the foundation stone that your film is on top of. And even when you meet people and say, "Hey, I made my film for $1," you know that's not true, because all that work that was there for free is still money. It's still works.
Someone had to pay for the gas in car, someone paid for the McDonald's coffee or whatever. Understanding that is very valuable and I think most filmmakers, including myself, don't want to do that. And so we go…
Ashley: Yeah, I know. I'm right there with you.
Martin: … we go into that kicking and screaming and having nightmares about it and not wanting to do it, but in the end you have to do it. And because of that I managed to make a film. So we managed to… we had all this money, when I say all this money it really wasn't very much money, but it was enough. So I'd been writing, this was all going on whilst I was writing Atomic Apocalypse thinking that we'd do this next. Then when I finally had that moment where I went to the lawyers and I said, "Can we do another movie?" They were like, "Yeah, yeah, yeah." I'm like, "We're doing Black Flowers. We're doing that." Because I've already got the script, I've got half the things. And then I phoned up Krista in New York and I said, "Look, I've got some money. Let's make a movie. Do you wanna go to Shasta and Montana?" She said yes.
Then cut to literally three weeks later we were there doing a recce. Because I thought if I don't spend the money now something will happen and then it will go. Like the lawyers will change their mind or the accountant will send me a huge bill or someone will die and something will go wrong. And so suddenly, it was very strange because just suddenly we had… the money was available. I don't imagine that will ever happen to me ever again, but… if I live to be a thousand. So that was a very boring way of financing the movie. We were trying to make that movie, it completely failed so we used it for another movie so we didn't have to give it back.
Ashley: Gotcha. So let's go back to the script here and the writing of it. You spend a couple of days in this very preliminary, then you spend some time in a word document. How much time do you spend in the word document and then ultimately, how much time do you spend in final draft actually churning out script pages?
Martin: Well, I'm just trying to think of the timescale. I mean, the thing is with movies, movies are getting longer and longer and longer. I read somewhere the other day that the average length of the movie now is 107 minutes. That's approximately 107 pages. But as filmmakers, we don't have a huge amount of money. So really you wanna make the shortest possible film you can make for the money which tells your story you wanna tell. I was aiming for 84 pages, and half of 84 is like 41 and half of that is, let's call it 20-ish. So I was putting my [inaudible 00:20:30] structures in, so I was thinking, okay, I need to get to page 20, then page 40, then page 60, then page 80 with a couple of pages leeway each way to add up to 84 and then 84 plus your titles and your credits is gonna be enough.
And as a director, I like my actors to improv a little bit. I like to try things out on set and you're gonna shoot extra stuff as you go along and then hopefully that'll end up with your nice 90 plus minute movie. So that was planned. I had my structural set out, I started writing the beat sheet, because I do a beat sheet. I put scene one, this happens, this dah, dah, dah, dah, dah, dah. And then you can move them all around until you've got the structure the way you want it. I'll probably spend a couple of weeks on that. I mean if I actually call up all my documents here, they'll have dates on them. So if you're that interested…
Ashley: Well, just… I'm just… just ballpark. I mean we're talking about three months or are we talking about three weeks?
Martin: Probably a month to get the… because I've done a lot of… I've written a lot of movies, so once I actually get into it, it goes very fast. Because I'll sit down and I'll write all of act one and then the first half of act two and the second half of act two and then act three in blocks, like as notes. Then I'll put it all together. And I'll just keep going around until I've got the plot the way I like it. Then I'll put go in and start putting in dialogue and stuff. Whilst I was doing all of that I was talking to Krista on the phone, on Skype I mean, and running some dialogue and things like that to see how the it comes together. Also, the earlier drafts had much more characters in. There were several more characters.
Then as you come along, you think, "Well, those two characters are serving the same purpose." So they meld together and they became one character and there's… that happened twice. So you're getting less characters, which gives the actors more to do, which is great. And obviously less mouths to feed, less hotel rooms, less aircraft flights. Then you're honing it and honing it. And then when we went off on the location recce, I saw a lot of things and I thought, "Okay, so this thing that I've seen that's perfect for this scene." So we'll tweak the scene to fit the location. And then we found some artifacts and items and things and I think, "Oh, that would look great in the film'" So we'd change the story to fit the location.
I mean, if you've got a huge budget, if you're Steven Spielberg, I don't think that happens very often, but when you haven't got a huge budget, if you see something that's amazing, then use it in your film, because it's a gift from God.
Ashley: Yeah. What was it like shooting in Montana just in general? Like you mentioned that you found like an abandoned gas station. How do you shoot… like in LA there would be a certain, you really would probably wanna get permits and contact the landlord. What is it like in Montana? There's a burned-out gas station; who owns it? How do you just show up there and start shooting?
Martin: Well, I mean I live in London and if you think LA has a lot of paperwork, then come to London because we'll beat you because we've got more. I was filming up the road, I live… I'm in London right now as I talk to you, and I was filming up the road for some pickup shots for The Gatehouse a few years ago. We were in a wood called Hampstead Heath and we were filming there and the police turn up with dogs and ask us what we're doing.
Ashley: And you're in the house?
Martin: No. We were in the woods, up the road. And this is London and we're in the woods and there's no one there and the police turn up with dogs and tell you, "You can't film here." But luckily we had a permit. But that was full on and you're like, "well, what would've happened if I hadn't got a permit, would they eat me? Hack my leg off?"
Ashley: Probably. Well, how does it compare to Montana?
Martin: Well, I mean, first of all, we filmed up in Mount Shasta, California. That's on the border with Oregon. It's very beautiful there.
Ashley: You just went to Montana for this bunker?
Martin: No. And some exteriors. Yeah, I mean the Montana Film Office were very helpful. We got in touch with them when we were driving around doing the recce, reconnaissance… the location scout. They said, "Come and have a meeting." So we came and had a meeting and they offered their location scout servicing for free. And the great thing is, if you go to a place where there's not many people, I mean, in the whole state of Montana, there's only 1 million people. So if you go somewhere where there's not many people, no one cares if you film. In LA, people don't want you to film because they want to make money out of you, but they don't really care that you're filming.
Whereas you go to Montana and people are excited that you're filming. So people will turn up to help and people would turn out to be extras and people will… if you say, "We're looking for this, any suggestions?" People will come back and say, "Hey, well my friend has that. Why don't you film there?" It's another way of filming. That's like when we did The Gatehouse, we went and filmed in the West of England in a place called Somerset and we filmed in the woods and no one stopped us and no one complained. And when we said, "Can we film in your shop?" people would say, "Yes, you can film in our shop." It's a totally, totally different experience. And if everyone was lovely… I mean, the truth is, it's a funny old thing.
Making film, as everyone knows is hard work, it's not like necessary work, it's not like saving the planet or anything like that, but it's hard work. We're all very superstitious and you don't wanna jinx it. You never want to say things like, "Oh, that was easy," until it's over. And now it's over and we shot it two years ago, I can say, "Nothing really badly went wrong." No one got electrocuted, no one got drowned, no one… you know, all those great things, no one did any of that. And the atmosphere on set was great because we were working with people who wanted to be there, who were happy to do the work and a bunch of very talented actors who had, as they say, threw down and worked hard and in the cold and the rain.
Well, it wasn't actually that rainy but in the cold. Yeah, it was a great experience. I would film in Montana again at the drop of a hat.
Ashley: Okay, perfect. And so with this screenplay, I'm curious did you approach any sort of genre requirements? I mean, certainly the post-apocalyptic, it's sort of a sub-genre, I guess, of Sci-fi, Mad Max. I mean, there's a history of these movies. Did you go back and review them? Are there any takeaways from these movies? Are there any things you tried to do differently, some tropes from these post-apocalyptic movies that you may be leaned into or didn't lean into? I'm just curious sort of just what your genre requirements were, how you approached the genre in general.
Martin: Yeah, sure. Totally. I mean, I thought Mad Max: Fury Road that came out a few years ago, I think that's one of my favorite films of the last 10 years. I think it's brilliant. The fascinating thing about that is people say it hasn't got much story in it. What they actually mean is it hasn't got much dialogue in it. It's got so much story in it; it's got tons of story in it. I thought it was brilliant. And I just really got the post-apocalyptic vibe and Mad Max 2 was great. So I went and watched Waterworld, The Postman, Book of Eli and The Road. I watched all those again and everything. The vast majority of them are a bit miserable. Like The Road is very depressing. The Book of Eli is pretty depressing and The Postman's a bit boring.
I liked Waterworld the best actually. That was great. And I thought, again, we can't out Waterworld, we don't have that size budget. So the genre tropes, I wanted to have all of those things. They're walking along a road and there's no one there. People have built their own costumes out of artifacts and there's a couple of nods to the role-playing game Gamma World. Like when we were kids, we used to play DND, Dungeons and dragons. And there was a post-apocalyptic version, which was called Gamma World, so we used to play that.
Ashley: I remember it, yeah.
Martin: And I've got two nods to Gamma World in the film, so if there's any Gamma World fans out there, which I doubt, but if there are, then they will see it and they'll go, "Oh, yes." And so I got all… I had that in it and I thought the thing we can bring to the post-apocalyptic world that no one else is really doing is one, a female led story, because I can't find any post-apocalyptic films that are female led with the possible exception of Mad Max: Fury Road. But even Furiosa is the secondary character, not the lead. So we thought, okay, let's have a female-led story and also let's put some humor into it. It's not a comedy, but there are humorous moments. And also let's make it positive.
So at the end it's good for humanity rather than a terrible miserable ending. Like most apocalyptic things are terribly depressing. And I thought, the news is depressing enough, I don't need my entertainment to be depressing as well.
Ashley: I'm curious, so when you took this movie to market, whether it be film festivals and then ultimately distributors, how did you find the reception in terms of the genre? I mean your last film was sort of a horror thriller. And then how did you find a post-apocalyptic Sci-fi movie? Just the reception. Were distributors more open, more interested in a post-apocalyptic Sci-fi or were they more interested in a horror movie? And same thing, even just fans and film festivals.
Martin: We've done very well at the film festivals, because we're still a small budget indie production company. But we played… we had our world premiere at Sitges International Film Festival, which is fantastic. It sold out, 450-seater, big audience. Then we had our UK premier Sci-fi London and Berlin Sci-fi and we had our US premiere, the World Fest in Houston. We get consistently great response from the audience. They love it. They really, really… you gotta like Sci-fi. If you're going there and you want to see, I don't know, something really depressing about people in costumes from 19, 1800s then this is the wrong film. But if you want some Mad Max meets Thelma and Louise, then this is the right film.
And the audiences you come along to Sci-Fi festivals and things like that, they understand genre and they… we've had on the whole very, very, very positive experience. Lots of people coming up and saying they thought it was a great film. Because it's an unexpected film. We've taken the post-apocalyptic genre and we've just twisted it a little bit to make it interesting. Because if we'd just done the same as everybody else, then we'd just done the same as everybody else. And as a director, it's very important for me to make films that only I could have made. So I don't think there's any other filmmaker in the world, whether you like my films or not, I don't think there's any other filmmaker in the world who makes films like I make films.
It's like being a painter, because my degree was Fine Art. When you paint a painting, you want it to look like one of your paintings. You don't want it to look like everybody else's painting, even though it might sell more.
Ashley: Well if you put it that way I don't know if it's such a bad thing. So in any event though how can people see Atomic Apocalypse, do you know what the release schedule is gonna be like?
Martin: Yes. It comes out on the 4th of February, so we are days imminently. I'm coming back to America for a little tour. We're gonna have five screenings in California, in Montana, and then we're gonna have a screening in LA at Magicopolis in Santa Monica on the 13th of February. And that's open to the public. Anyone can come along and we all be there. Crystal will be there, some of the other actors and crew will be there and they have a bar and we'll stay there until they physically remove us from the premises.
Ashley: Good to know. So people can show up late. Perfect. And what's the best way for people to keep up with what you're doing? Twitter, Facebook, a blog, I will round all that stuff up for the show notes.
Martin: Yeah. I'm on all of those. Twitter… I mean I'm just basically Martin Gooch on everything, so I'm easy to find. I'm terrible at Twittering. I just tend to like other people's stuff. I've got to get better at Twitter. Instagram, I find incredibly dull, because I'm so bored of looking at other people's lives. I don't wanna see what they're doing. I don't care.
Ashley: Yeah. I'm with you. One follow-up question that I thought of that you were talking at the top of the interview, you mentioned you were a judge for the Santa Barbara Film Festival. I'm curious now, you've seen it from both sides of the equation as a film maker submitting films and going to films and now you've been on the other side as a judge. Are there any takeaways, any advice you have sort of parting advice for filmmakers now that you've seen it from the judge's perspective and from the filmmaker perspective?
Ashley: Yeah. Don't make boring films. We have to sit through them. Yeah, if your film's more than an hour and a half and it's an indie, honestly, cut it down. Phone me up and I'll come around and I'll just edit your film for you. I'll cut it out like every third scene, I just cut it.
Ashley: Well, it's funny you give that advice because with screenplays it's the same thing. I get emails all the time, "Hey, my screenplay is 150 pages," "Hey, it's 180 pages." And that's my first piece of advice is like, "Listen, it might be The Godfather, but it's probably not, so you probably need to get it down to that 90-page threshold." So anyways, good advice. Well Martin, always good to talk with you. Good luck with this film and I look forward to having you on as a fourth time guest in the future.
Martin: Yeah, yeah, yeah. More movies to come.
Ashley: Exactly. So Martin, take it easy. We'll talk to you later.
Martin: Thanks man. Cheers.
Ashley: Thank you. Bye.
Ashley: I just wanna talk quickly about SYS Select. It's a service for screenwriters to help them sell their screenplays and get writing assignments. The first part of the service is the SYS Select screenplay database. Screenwriters upload their screenplays along with a logline, synopsis and other pertinent information like budget and genre, and then producers search for and hopefully find screenplays they wanna produce. Dozens of producers are in the system looking for screenplays right now. There have been a number of success stories come out of this service, you can find out about all the SYS Select successes by going to www.sellingyourscreenplay.com/success. Also on SYS podcast Episode #222, I talk with Steve Deering who was the first official success story to come out of the SYS Select database.
When you join SYS Select you get access to the screenplay database along with all the other services that we're providing to SYS Select members. These services include the newsletter, the monthly newsletter goes out to a list of over 400 producers who are actively seeking writers and screenplays. Each SYS Select member can pitch one screenplay in this monthly newsletter. We also provide screenwriting leads, we have partnered with one of the premiere paid screenwriting leads services, so I can syndicate their leads to SYS Select members. There are lots of great paid leads coming in each week from our partner, recently we've been getting five to 10 high quality paid leads per week. These leads run the gamut.
There's producers looking for a specific type of spec script to producers looking to hire a screenwriter to write up one of their ideas or properties. They are looking for shorts, features, TV and web series, pilots all types of projects. If you sign up for SYS Select, you'll get these leads emailed directly to you several times per week. Also, you get access to the SYS Select forum where we will help you with your logline and query letter and answer any screenwriting related questions that you might have. We also have a number of screenwriting classes that are recorded and available in the SYS Select forum. These are all the classes that I've done over the years, so you'll have access to those whenever you want once you join.
The classes cover every part of writing your screenplay from concept to outlining, to the first act, second act, third act as well as other topics like writing short films and pitching your projects in person. Once again, if this sounds like something you'd like to learn more about, please go to www.sellingyourscreenplayselect.com.
Anyway, that's the show for today. Thanks again for listening. And please again, if you have a minute, please do check out the Kickstarter campaign and again, that is www.theridesharekiller.com. Thanks.
Next post: SYS Podcast Episode 316: With Writer/Director Martin Gooch
Previous post: Writing The Low Budget Feature: How I Kept The Rideshare Killer On Budget


Located around 4 hours west of the traditional French alpine reports Super Besse is a hidden gem.
The 1960s purpose built ski resort has a reputation for not being the prettiest of places. Rustic log cabins are replaced by concrete but not in an aesthetically unpleasing way. A location with unique charm nestled in the footprint of a long extinct volcano.
With a maximum altitude of 1,860m its not as snow sure as some of the higher and more commercial resorts but peak season it has sufficient snow cover and some 350 snow cannons to keep all its main pistes open. They seemed to have crammed in a little of everything from extensive cross country tracks to a snow park, jumps and a 2km long Tyrolienne situated close to the summit for those us more daring and light enough! When viewed from the highest vantage it feels a little like being on an iceberg surrounded by green rolling vistas.
Given its relative low altitude The approach to the resort is akin to a leisurely drive in wales with not a switch back or hair raising mountain clinging road in sight. Getting into the village does not require nerves or steel and when we arrived snow chains and winter tyres were not needed.
The four main selling points of this resort are its location, Motor home accommodation's, night skiing opportunity and over all value for money!
1. Its not all about the money!
Far and away the cheapest ski resort we have found to date. A days ski pass including insurance sets you back only €35 (€32.50 ex insurance) per person and for an extra €7.50 you have the option to ski under the flood lights until 8.45pm. In addition a coffee break or lunch stop at one of the restaurants wont break the bank. You can expect significant change from €10 for 2 coffees which is rarity in Alpine resorts.
Super Besse is situated in the Massif Central area of France and within the Grand Sancy Ski domain. Being centrally located its only a 7 hour drive (doing Motor Home speeds) from Le Harve and Caen which is handy if you choose to take the overnight ferry from Portsmouth because you can be in resort by late lunch without a lot of effort.
Unlike a lot of resorts the motor home aire is actually better positioned than a lot of the permanent accommodation's. Despite arriving during the busiest week of the season when the French and English schools were on half term break the aire was not full and could comfortably accommodate close to 100 vans.
Most pitches had access to mains power and the overnight costs were reasonable. A single night stay will set you back €9.60 which includes free water and waste disposal.
Power can be purchased for €2.50 for 4 hours which whilst not cheap use of generators was not frowned upon.
The aire also offers a daily gas rental delivery each morning which is handy if you run short (note you will need to sign a French gas rental agreement).
All facilities can be paid for at the aire entry via an automated machine. The pay point operates in multiple languages so limited French is not an issue. Barrier entry to the aire requires input of the code purchased at the little hut on arrival and the whole area is floodlit over night and felt very safe. It was a friendly little community.
One of the biggest perks of the resort has to be the night skiing. As soon as the sun sets a number of pistes are illuminated and the snow sports continue. That includes the jumps park for those with skillz or no fear. The only downside of this is the condition of the pistes. After a long day of use during sunny days the pistes do become a bit moguley and slushy which then refreezes at night so evening descents can be a little sketchy.
During our stay we didn't see another English van and the resort does not seem popular with the Brits. English speaking attendants at the ski pass shop seems to not be mandatory (as you would expect in larger resorts) and we found English speakers were not in abundance so our French skills were tested. Having said that everyone seemed more than happy to tolerate our broken French and we didn't feel uncomfortable. Advice would be to at least try though!
This resort is not huge and with only 45k of pistes and a smattering of lifts some may get a little bored of doing the same runs over and over again but its layout, services, relative cheapness, location and family friendly vibe make it somewhere we shall be returning to in the future.


1. Prepare a study of Indian Banking Industry and analyse the changes that took place in the relationship practices of this industry?
2. Explain the concepts of customer retention and customer recall management?
The foundation of Shopper's Stop Ltd. was laid on 27th October, 1991 by K. Raheja Corp. Group of Companies. Being amongst India's biggest hospitality and real estate players, the Group sets another milestone with their lifestyle venture. The objective was to create a fashion and lifestyle store for the entire brands for the same. It tried to bridge the gap between the unprofessionally managed and poorly stocked merchandise and ill-mannered staff, and the growing urban upper middle class who had money to spend but were asking for a quality environment. The objective was to create a fashion and lifestyle store for the entire brands. It tried to bridge the gap between the unprofessionally managed and poorly stocked merchandise, ill-mannered staff and the growing urban upper middle class who had money to spend but were asking for a quality environment.
From its inception, Shopper's Stop has progressed from being a single brand shop to becoming a leading fashion & lifestyle store for the family. A pioneer of organized retailing in India, today, it has become the highest benchmark for the Indian retail industry. Its stores are present across various Indian cities such as Bangalore, Hyderabad, Jaipur, Delhi, Chennai, Mumbai, Pune, Gurgaon, and Kolkata. It has a national presence of over 6,00,000 square feet of retail space, stocking over 250 brands of garments and accessories.
In fact, the company's continuing expansion plans aim to help it meet the challenges of the retail industry in an even better manner than it does today. Its vision is to be a global retailer in India and maintain its No.1 position in the Indian market in the Department store category. Being at the helm of a customer centric business, there is a strong emphasis on customer satisfaction which, in turn, translates into taking all aspects of the business very seriously.
The retail chain major is eyeing 50% sales growth from its CRM initiatives. The company has also line up an aggressive expansion plan, targeting smaller towns and cities in the country. According to Managing Director and CEO of the company, it has given a new direction to its CRM initiatives after acquiring business intelligence software called "Business Solutions".
The new software helps generate intelligent data from Shopper's Stop customer base of about 2,30,000. The company then collects this data and touches base with customers via direct mailers informing them about the upcoming events. A company release says: "Last year, about 50 % of our sales came from repeat customers and this year too we are expecting this number to grow ". The company claims that it has taken its CRM initiatives to a new height and now calls its loyalty programmes.
Overanalysing of the company's sales trends and pattern helped realize that most of the sales were coming from the old customers primarily through repeat purchases it thought of focusing on those customers. The company tried to leverage data by providing information and the company may ultimately be benefited. As, if a customer had bought a pair of trousers, it tells him about a new range of shirts that it has just brought into the store.
• Exclusive cash counters so that they can spend more time shopping rather than waiting in a line.
The company believes in providing the best experiences possible, including the best benefits and privileges. The programme gets as rewarding as one makes it since it depends on the membership status which is upgraded when one qualifies with the necessary purchases during the membership period.
Co-branded CRM initiatives: Shopper's Stop has been launching several schemes to benefit its profitable customers and has been coming up in partnership with several leading players who matter for retailing industry. One such programme partner is Citibank.
First citizen Citibank debit card: The First Citizen ATM/debit card is India's first co-branded ATM/debit card in the retail sector. While this card can be used as a regular debit card and at an ATM to withdraw cash, it also helps a customer collect reward points every time he purchases merchandise at any shopper's stop outlet. This also provides automatic membership to First Citizen Shopper's Stop Loyalty programme for those who are not First Citizen members yet. The company had also gone in for massive IT initiative to support the customer support it had planned for. It chose software tools for facilitating, the analysis of the customer data. They have been using a combination of business objects and the Statistical Analysis System (SAS) solutions for trend analysis, promotion, management, consumer behaviour, segmentation, buying basket analysis, profitability and lifecycle analysis.
1. Shopper's Stop was the first among the organized retail players to initiate CRM practices. What do you find from the above case study to substantiate this view?
2. Shopper's Stop has initiated many things in the direction of keeping customers for life. What are those initiatives?
1. "CRM programmes are a costly affair, but the long-term reward it generates is much more beneficial than the revenue it generates". How far do you agree with the statement and why?
2. Consider yourself as a Business Manager of an insurance company in a city. How would you design a system to study customer feedback of your services and delivery? Explain in full detail.
A) Infosys was recruiting a German. When the candidate was asked why he wanted to join Infosys, he replied he wanted to join the company where Mr. Narayana Murthy works. This shows that the employees remain with the organization with full dedication as long as they are taken care of properly.
B) Once the CEO of Relocation Management Resources found one of his best customer service managers during a frustrating experience at the airport. Upon finding out his flight was cancelled, the CEO called the airline company to complain –bitterly. The women who took the call remained poised despite the CEO's self-described ranting and raving. By the end of the conversation, the CEO made the woman a job offer, which she later accepted.
C) Cognizant, an IT company celebrates its major milestones with employees, usually by giving them a choice of gifts such as TVs, DVD players, and music systems. This is because the company believes that employee delight is the basis for Customer Delight in a service company. Cognizant believes this is the only way to keep employees happy and make them feel to be a part of the company which may otherwise seem impersonal to most employees if they only maintain an arm's length relationship.


Watch Nigeria's football stars of tomorrow shine today.
All is now set for the quarter final rounds of the GTBank-Lagos State Principals Cup Season 6.
With sixteen teams left in the tournament, the 2015 GTBank-Lagos State Principals' Cup is about to get even more exciting. Watch Nigeria's future male and female football stars play in the quarter – final games of the lively competition on Monday, February 23 and Tuesday, February 23 at the Agege Stadium, 1, Ositelu Street, Off Agege Road, Agege, Lagos.
Four games in the male and female categories will be played on each day. Head below for the full match schedule and see photos and more updates here.
GTBank Principals Cup is an annual secondary school football competition geared towards the development of grassroots football, the discovery of young football talents and fostering camaraderie amongst secondary school students. It also provides a platform for identifying, nurturing, grooming young and talented players as well as helping students actualize their dream of becoming professional footballers.
GTBank also compliments the Principals Cup tournament with an annual residential coaching programme known as "Camp GTBank". Camp GTBank is a football developmental programme designed to discover, sharpen and cultivate the skills of outstanding talents of the GTBank Lagos State Principals Cup and Master's Cup, drawing on the experience of top coaches from European clubs.


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Recently, one of my largest errors in affiliate marketing hit me front and center. Even though I make a quite comfortable living as a full-time affiliate marketer, this mistake has expense me drastically more than the years. 1.Prior to something else, you will need to choose which niche or specialty you want to go into. This will help you concentrate on the solutions you will be selling to your shoppers. This is also significant since you have to have to have adequate knowledge to be capable to sell your products well. Marketers who present their products but have tiny information about it typically don?t succeed right away.
Simply because of the intense competition in affiliate advertising and marketing, it is vital that one should equip himself with the most up-to-date approaches and methods that will catapult income like in no way before. This post will give you the rundown on three of the simplest however most successful affiliate promoting techniques on how to succeed: We all make mistakes, it really is a reality of life. It is no large deal in the complete scheme of points as long as we find out from our mistakes and move forward. The very same goes with affiliate marketing because absolutely everyone will probably make errors at initially, but as long as you fix them, it's no major deal.
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Freelancing Web Development Projects – The similar goes with affiliate promoting considering that everyone will possibly make blunders at 1st, but as extended as you fix them, it's no big deal.


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DatsiK
All the concerts from DatsiK
Follow this artist and we'll let you know when they have concerts.
If you don't know Datsik by now, you best be learning. Datsik has been taking the dubstep scene by storm, blowing up dance floors around the globe with his original style of hip-hop future-tech bangers. In 2009 alone, Datsik had over 7 number one releases on Beatport, and vinyl sales through the roof on many other sites such as Chemical Records, Red-Eye and Juno. Aside from that, he has also done remixes for some of the biggest names in the scene such as the Crystal Method, Freestylers, Bassnectar, Noisia, Diplo, the Wu-tang Clan, and Apex from the critically acclaimed Lifted Music label; not to mention countless collaborations with some of the hottest producers in the scene. With multiple anthems under his belt, countless plays from some of the biggest DJ's, and an endless perseverance to reach that next step, it is safe to say that Datsik has proven himself to be one of the best dubstep artists around… and he is here to stay.
Bassnectar
Alison Wonderland
Knife Party
Concerts in Amsterdam
Concerts in Utrecht
Concerts in Tilburg
Concerts in Groningen
Concerts in Hoofddorp
Concerts in Rotterdam
Concerts in Nijmegen
Concerts in Eindhoven


Some kinds of floor need special care. Sorma has conceived floor-polishes and stone protectors in order to maintain surfaces value. Sorma's products also guarantee a great resistance to traffic and washing; they even resist to alcohol.


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Transcription is a beneficial service for several industries but in law, transcription records are more than just helpful. They're often a necessary link in the chainÔøΩ a crucial reference for lawyers as they write a patent application, or prepare for a solution to a dispute, or build their arguments in court. And, in some cases, those documents go on to become historical record for landmark decisions. Take for instance New York Times v. Sullivan, the 1964 ruling that requires all libel and defamation cases to show proof of intent or recklessness. In an era where social media has led to a 300% increase in libel cases, the original decision is still foundational and referenced frequently. Thus, whether it's a pivotal case, deposition, record of evidence, or simple note-taking, legal transcription matters greatly.
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Exploring the sounds of the Middle East
Submitted by Josh Grossman on Thu May 3 3:35pm
This Sunday, May 6 at The Rex Hotel, we are excited to co-present, along with the Canada-Israel Cultural Foundation, the 2018 Israeli Jazz Showcase, as part of the wider Spotlight on Israeli Culture. Sunday's event will mark the 4th Israeli Jazz Showcase; with each edition of the Showcase we aim to present artists who accurately represent the diversity of music coming out of Israel and the wider Middle East - and I wonder if this year's artists provide the widest variety yet.
Kicking off the evening at 7:30 pm is vocalist Aviva Chernick, in what she calls "a reimagining of traditional Balkan Ladino repertoire along with original Hebrew melodies." She'll be joined by Ernie Tollar (woodwinds), Justin Gray (bass), Naghmeh Farahmand (percussion) and Derek Gray (drums) - a group of musicians who represent an impressive range of musical traditions even before tackling the repertoire Aviva has put together. I became familiar with Aviva through her work as a long-time member of the ensemble Jaffa Road, but the breadth of her work in impressive - she's performed with top musicians in a variety of world music traditions, blues, jazz, pop, and folk; most recently I heard her name as part of the cast of a Soundstreams production about Claude Vivier!
Aviva's instrument is pristine and flexible (as it must be to perform so easily in so many different styles), readily soaring overtop of the ensemble as the lead line or working within the ensemble, almost as another horn. Her most recent album, When I Arrived You Were Already There, also shows off the creativity which drives her (and which previously earned her and her co-writers a John Lennon International Songwriting Grand Prize) - the performances give new life to what may be familiar texts. The full range of her voice is sure to be on display on Sunday; it will be a treat to hear her perform, with this particular group of musicians, in the intimate setting of The Rex.
The Showcase "headliner" this year is trumpeter Itamar Borochov, who will bring along bandmates Rob Clearfiled on piano, Sam Weber on bass and Francesco Ciniglio on drums. It was his association with Yemen Blues - he served as arranger and co-producer for the acclaimed world music sensation for three albums - which first brought Itamar's name on to my radar. But his approach to writing and his approach to playing the trumpet stand on their own. A fluid player with a beautiful sound, his soloing is impressively melodic, whether on an up-tempo contemporary jazz tune or a more soulful tune drawn from the Muslim, Jewish or Christian traditions which surrounded him growing up in Jaffa, Israel.
Listening again to his 2016 release Boomerang, I'm impressed first (and fundamentally) by the trumpet playing - melody rules here, regardless of the style of the piece. But the variety of music is also unique: there are post-bop jazz tunes; traditional melodies from various traditions; and songs clearly inspired by the land of his youth. Itamar sites a variety of influences when it comes to his music-making - his father is a musician, so Itamar's toys when growing up were musical instruments of all sorts; he talks about listening to blues and jazz, but also learning Arabic scales. More recently, he's worked closely with a Moroccan Jewish cantor and Morocco's Innov Gnawa, which performs Moroccan spiritual music with roots in Islam (he will, in fact, produce their next album). And rather than let these various influences create a strange mishmash of musical traditions, Itamar carefully chooses musical influences from one tune to the next - creating an interesting and always compelling sound.
Particularly exciting to me about the combination of musicians we get to hear on Sunday is their fresh approach to mixing jazz traditions with Middle Eastern traditions. This is music free of cliche, and which I suggest will defy any preconceived notions of how Israeli jazz sounds.
This has been an outstanding week of music, with two excellent Special Projects presentations last weekend (kudos again to Adrean Farrugia and Aline Homzy for all of their work) - I look forward to wrapping up our pre-Festival activity on Sunday with what is sure to be a beautiful night of music.
The Israeli Jazz Showcase is this Sunday, May 6, starting at 7:30 pm at The Rex Hotel. Complete details on our website. I hope to see you there!


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Salomona borneensis är en insektsart som beskrevs av Willemse, C. 1959. Salomona borneensis ingår i släktet Salomona och familjen vårtbitare. Inga underarter finns listade i Catalogue of Life.

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