Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Referenceless Rate-Distortion Modeling with Learning from Bitstream and
  Pixel Features   Generally, adaptive bitrates for variable Internet bandwidths can be obtained
through multi-pass coding. Referenceless prediction-based methods show
practical benefits compared with multi-pass coding to avoid excessive
computational resource consumption, especially in low-latency circumstances.
However, most of them fail to predict precisely due to the complex inner
structure of modern codecs. Therefore, to improve the fidelity of prediction,
we propose a referenceless prediction-based R-QP modeling (PmR-QP) method to
estimate bitrate by leveraging a deep learning algorithm with only one-pass
coding. It refines the global rate-control paradigm in modern codecs on
flexibility and applicability with few adjustments as possible. By exploring
the potentials of bitstream and pixel features from the prerequisite of
one-pass coding, it can reach the expectation of bitrate estimation in terms of
precision. To be more specific, we first describe the R-QP relationship curve
as a robust quadratic R-QP modeling function derived from the Cauchy-based
distribution. Second, we simplify the modeling function by fastening one
operational point of the relationship curve received from the coding process.
Third, we learn the model parameters from bitstream and pixel features, named
them hybrid referenceless features, comprising texture information,
hierarchical coding structure, and selected modes in intra-prediction.
Extensive experiments demonstrate the proposed method significantly decreases
the proportion of samples' bitrate estimation error within 10% by 24.60% on
average over the state-of-the-art.

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The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
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The categories of this paper are: funct-an
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The categories of this paper are: cmp-lg
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The categories of this paper are: alg-geom
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The categories of this paper are: quant-ph
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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: mtrl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex
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The categories of this paper are: nlin
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The categories of this paper are: nucl-th