Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video
  Compression   Conventional video compression methods employ a linear transform and block
motion model, and the steps of motion estimation, mode and quantization
parameter selection, and entropy coding are optimized individually due to
combinatorial nature of the end-to-end optimization problem. Learned video
compression allows end-to-end rate-distortion optimized training of all
nonlinear modules, quantization parameter and entropy model simultaneously.
While previous work on learned video compression considered training a
sequential video codec based on end-to-end optimization of cost averaged over
pairs of successive frames, it is well-known in conventional video compression
that hierarchical, bi-directional coding outperforms sequential compression. In
this paper, we propose for the first time end-to-end optimization of a
hierarchical, bi-directional motion compensated learned codec by accumulating
cost function over fixed-size groups of pictures (GOP). Experimental results
show that the rate-distortion performance of our proposed learned
bi-directional {\it GOP coder} outperforms the state-of-the-art end-to-end
optimized learned sequential compression as expected.

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The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
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The categories of this paper are: ao-sci
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The categories of this paper are: nucl-th
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The categories of this paper are: adap-org
3
The categories of this paper are: physics
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The categories of this paper are: q-bio
2
The categories of this paper are: math
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The categories of this paper are: stat
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The categories of this paper are: supr-con
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The categories of this paper are: quant-ph
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The categories of this paper are: q-fin
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The categories of this paper are: acc-phys
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The categories of this paper are: mtrl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: gr-qc