Video Restoration
Overview
Video restoration studies how to recover useful visual information from degraded footage, including motion blur, low resolution, noise, compression artifacts, weather, flicker, and damaged archival film. Methods use temporal alignment and fusion, recurrent networks and transformers, physical models of how degradation forms, and diffusion or flow-matching generative priors; some also draw on metadata, reference frames, or other sensors. Evaluation spans settings such as super-resolution, deblurring, HDR reconstruction, and object removal, using benchmarks such as REDS, GoPro, and VFHQ alongside real-world footage. A central challenge is balancing perceptual detail and realistic generation with fidelity to the original scene, temporal stability, and the speed and memory needed for long or high-resolution video.
Latest papers
59 papers8 papers in the last four weeks, up 14% on the four weeks before. 0.0% of all new papers.