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AIVC: Artificial Intelligence based Video Codec

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arxiv 2202.04365 v3 pith:W3POK3XA submitted 2022-02-09 cs.NE eess.SP

Théo Ladune , Pierrick Philippe This is my paper · ORCID
classification cs.NEeess.SP
keywords aivcvideocodeccodingend-to-endablationartificialautoencoders
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This paper introduces AIVC, an end-to-end neural video codec. It is based on two conditional autoencoders MNet and CNet, for motion compensation and coding. AIVC learns to compress videos using any coding configurations through a single end-to-end rate-distortion optimization. Furthermore, it offers performance competitive with the recent video coder HEVC under several established test conditions. A comprehensive ablation study is performed to evaluate the benefits of the different modules composing AIVC. The implementation is made available at https://orange-opensource.github.io/AIVC/.

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Cited by 1 Pith paper

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  1. Exploiting Latent Properties to Optimize Neural Codecs

    cs.CV 2025-01 conditional novelty 6.0 of 10

    Using uniform lattice grids for quantization and entropy-gradient latent shifting improves rate-distortion performance of off-the-shelf neural codecs by 1-3% without retraining.

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