Neural Video Compression

Neural video compression aims to leverage deep learning to achieve superior rate-distortion performance compared to traditional codecs like H.266/VVC. Current research focuses on improving efficiency through techniques such as implicit neural representations (INRs), transformer architectures, and optimized entropy modeling, often incorporating hierarchical B-frame coding and content-adaptive strategies. These advancements are driving progress towards practical, real-time neural video codecs for mobile devices and specialized applications like satellite imagery compression, potentially revolutionizing video storage and transmission.