RT-NeRV: Rethinking Hybrid Neural Representations for Video via Residual Tokenization

ArXi:2403.12401v2 Announce Type: replace Neural Representations for Videos(NeRV) have emerged as a promising paradigm for video compression by representing videos as compact neural networks with efficient decoding. Hybrid NeRV methods further improve reconstruction quality through content adaptive embeddings, but still struggle to preserve fine details at low bitrates. A key limitation is that shallow residual in formation, although highly beneficial for reconstruction, is costly to transmit in its continuous form and is therefore underutilized.