no code implementations • 5 Jul 2022 • Ruoyu Feng, Xin Jin, Zongyu Guo, Runsen Feng, Yixin Gao, Tianyu He, Zhizheng Zhang, Simeng Sun, Zhibo Chen
Learning a kind of feature that is both general (for AI tasks) and compact (for compression) is pivotal for its success.
no code implementations • 25 Jan 2022 • Xin Jin, Ruoyu Feng, Simeng Sun, Runsen Feng, Tianyu He, Zhibo Chen
Traditional media coding schemes typically encode image/video into a semantic-unknown binary stream, which fails to directly support downstream intelligent tasks at the bitstream level.
no code implementations • 26 Dec 2021 • Zongyu Guo, Runsen Feng, Zhizheng Zhang, Xin Jin, Zhibo Chen
In this paper, we present the first neural video codec that can compete with the latest coding standard H. 266/VVC in terms of sRGB PSNR on UVG dataset for the low-latency mode.
no code implementations • NeurIPS 2021 • Runsen Feng, Zongyu Guo, Zhizheng Zhang, Zhibo Chen
We show that the flow prediction module can largely reduce the transmission cost of voxel flows.
no code implementations • 12 Apr 2021 • Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Quantization is one of the core components in lossy image compression.
no code implementations • 19 Nov 2020 • Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
In this paper, we propose the concept of separate entropy coding to leverage a serial decoding process for causal contextual entropy prediction in the latent space.