Recurrent Video Super Resolution

Recurrent video super-resolution (VSR) aims to enhance the resolution of low-resolution videos by leveraging temporal information across frames, improving upon frame-by-frame approaches. Current research focuses on improving the efficiency and stability of recurrent networks, exploring architectures like cascaded temporal updating and Kalman-inspired feature propagation to reduce computational cost and enhance temporal consistency, while also incorporating codec information to further optimize processing of compressed videos. These advancements are significant for applications requiring real-time processing, such as video streaming and surveillance, where efficient and high-quality super-resolution is crucial.