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 …

For neural video codec, it is critical, yet challenging, to design an efficient entropy model
which can accurately predict the probability distribution of the quantized latent …

Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper
presents a novel framework to effectively explore the physical haze priors and aggregate …

Real driving-video dehazing poses a significant challenge due to the inherent difficulty in
acquiring precisely aligned hazy/clear video pairs for effective model training especially in …

The outdoor vision systems are frequently contaminated by rain streaks and raindrops,
which significantly degenerate the performance of visual tasks and multimedia applications …

Almost all digital videos are coded into compact representations before being transmitted.
Such compact representations need to be decoded back to pixels before being displayed to …

Self-supervised video denoising has seen decent progress through the use of blind spot
networks. However, under their blind spot constraints, previous self-supervised video …

Video dehazing is a critical research area in computer vision that aims to enhance the
quality of hazy frames, which benefits many downstream tasks, eg semantic segmentation …

Video Compression (VC) is a significant aspect of multimedia technology, in which the goal
to minimize the size of video data, while also preserving its perceptual quality, for effective …

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 …