Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-end Neural Video Coding Using a Compound Spatiotemporal
  Representation   Recent years have witnessed rapid advances in learnt video coding. Most
algorithms have solely relied on the vector-based motion representation and
resampling (e.g., optical flow based bilinear sampling) for exploiting the
inter frame redundancy. In spite of the great success of adaptive kernel-based
resampling (e.g., adaptive convolutions and deformable convolutions) in video
prediction for uncompressed videos, integrating such approaches with
rate-distortion optimization for inter frame coding has been less successful.
Recognizing that each resampling solution offers unique advantages in regions
with different motion and texture characteristics, we propose a hybrid motion
compensation (HMC) method that adaptively combines the predictions generated by
these two approaches. Specifically, we generate a compound spatiotemporal
representation (CSTR) through a recurrent information aggregation (RIA) module
using information from the current and multiple past frames. We further design
a one-to-many decoder pipeline to generate multiple predictions from the CSTR,
including vector-based resampling, adaptive kernel-based resampling,
compensation mode selection maps and texture enhancements, and combines them
adaptively to achieve more accurate inter prediction. Experiments show that our
proposed inter coding system can provide better motion-compensated prediction
and is more robust to occlusions and complex motions. Together with jointly
trained intra coder and residual coder, the overall learnt hybrid coder yields
the state-of-the-art coding efficiency in low-delay scenario, compared to the
traditional H.264/AVC and H.265/HEVC, as well as recently published
learning-based methods, in terms of both PSNR and MS-SSIM metrics.

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The categories of this paper are: math-ph
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The categories of this paper are: stat
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The categories of this paper are: astro-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: gr-qc
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The categories of this paper are: solv-int
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The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: atom-ph
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The categories of this paper are: q-bio
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The categories of this paper are: supr-con
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The categories of this paper are: patt-sol
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The categories of this paper are: q-alg