3-D Context Entropy Model for Improved Practical Image Compression

Guo Zongyu
Guo Zongyu
Wu Yaojun
Wu Yaojun
Feng Runsen
Feng Runsen

CVPR Workshops, pp. 520-523, 2020.

Cited by: 0|Views22
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Abstract:

In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthened with residual structures. In short, we make three noteworthy improvements here. First, we propose a 3-D context entropy model which can take advantage of kn...More

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