Web: http://arxiv.org/abs/2106.12954

Jan. 14, 2022, 2:11 a.m. | Chuanmin Jia, Ziqing Ge, Shanshe Wang, Siwei Ma, Wen Gao

cs.LG updates on arXiv.org arxiv.org

End-to-end optimized neural image compression (NIC) has obtained superior
lossy compression performance recently. In this paper, we consider the problem
of rate-distortion (R-D) characteristic analysis and modeling for NIC. We make
efforts to formulate the essential mathematical functions to describe the R-D
behavior of NIC using deep networks. Thus arbitrary bit-rate points could be
elegantly realized by leveraging such model via a single trained network. We
propose a plugin-in module to learn the relationship between the target
bit-rate and the binary representation for the latent variable of auto-encoder.
The proposed …

arxiv compression for modeling neural rate

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