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CANF-VC: Conditional Augmented Normalizing Flows for Video Compression. (arXiv:2207.05315v3 [cs.CV] UPDATED)
Aug. 16, 2022, 1:13 a.m. | Yung-Han Ho, Chih-Peng Chang, Peng-Yu Chen, Alessandro Gnutti, Wen-Hsiao Peng
cs.CV updates on arXiv.org arxiv.org
This paper presents an end-to-end learning-based video compression system,
termed CANF-VC, based on conditional augmented normalizing flows (CANF). Most
learned video compression systems adopt the same hybrid-based coding
architecture as the traditional codecs. Recent research on conditional coding
has shown the sub-optimality of the hybrid-based coding and opens up
opportunities for deep generative models to take a key role in creating new
coding frameworks. CANF-VC represents a new attempt that leverages the
conditional ANF to learn a video generative model …
More from arxiv.org / cs.CV updates on arXiv.org
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