Neural Video Compression using GANs for Detail Synthesis and Propagation. (arXiv:2107.12038v3 [eess.IV] UPDATED)

We present the first neural video compression method based on generative
adversarial networks (GANs). Our approach significantly outperforms previous
neural and non-neural video compression methods in a user study, setting a new
state-of-the-art in visual quality for neural methods. We show that the GAN
loss is crucial to obtain this high visual quality. Two components make the GAN
loss effective: we i) synthesize detail by conditioning the generator on a
latent extracted from the warped previous reconstruction to then ii) …

arxiv compression gans video video compression