The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …

Abstract Neural Video Compression (NVC) has achieved remarkable performance in recent
years. However, precise rate control remains a challenge due to the inherent limitations of …

Neural video codecs have recently become competitive with standard codecs such as HEVC
in the low-delay setting. However, most neural codecs are large floating-point networks that …

Most existing neural video codecs (NVCs) only extract short-term temporal context by optical
flow-based motion compensation. However, such short-term temporal context suffers from …

Residual coding has gained prevalence in lossless compression, where a lossy layer is
initially employed and the reconstruction errors (ie, residues) are then losslessly …

Most existing image compression approaches perform transform coding in the pixel space to
reduce its spatial redundancy. However they encounter difficulties in achieving both high …

This paper provides a survey of the latest developments in visual signal coding and
processing with generative models. Specifically, our focus is on presenting the advancement …

Learned B-frame video compression aims to adopt bi-directional motion estimation and
motion compensation (MEMC) coding for middle frame reconstruction. However, previous …

As the amount of surveillance video data increases at an exponential rate, the need for
efficient video compression algorithms becomes increasingly urgent. The inter-frame …

With the high demands for video streaming, recent years have witnessed a growing interest
in utilizing deep learning for video compression. Most existing neural video compression …