11 citations · 21 across the 3 of their papers we have counts for
5 papers
Enhanced Neural Video Representation Compression Across Extreme Complexity and Quality Scales
Ho Man Kwan, Tianhao Peng, Fan Zhang +3
Implicit neural representations (INRs) have recently emerged as a promising approach to video compression, delivering competitive rate-distortion performance alongside rapid decodi…
Ultra-lightweight Neural Video Representation Compression
Ho Man Kwan, Tianhao Peng, Ge Gao +4
Recent works have demonstrated the viability of utilizing over-fitted implicit neural representations (INRs) as alternatives to autoencoder-based models for neural video compressio…
NVRC: Neural Video Representation Compression
Ho Man Kwan, Ge Gao, Fan Zhang +2
Recent advances in implicit neural representation (INR)-based video coding have demonstrated its potential to compete with both conventional and other learning-based approaches. Wi…
Immersive Video Compression using Implicit Neural Representations
Ho Man Kwan, Fan Zhang, Andrew Gower +1
Recent work on implicit neural representations (INRs) has evidenced their potential for efficiently representing and encoding conventional video content. In this paper we, for the…
HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
Ho Man Kwan, Ge Gao, Fan Zhang +2
Learning-based video compression is currently a popular research topic, offering the potential to compete with conventional standard video codecs. In this context, Implicit Neural…