Towards Redundancy Reduction in Diffusion Models for Efficient Video Super-Resolution

ArXi:2509.23980v2 Announce Type: replace Diffusion models have recently shown promising results for video super-resolution (VSR). However, directly adapting generative diffusion models to VSR can result in redundancy, since low-quality videos already preserve substantial content information. Such redundancy leads to increased computational overhead and learning burden, as the model performs superfluous operations and must learn to filter out irrelevant information.