VRT: A Video Restoration Transformer

Understand

Video restoration (e.g., video super-resolution) aims to restore high-quality frames from low-quality frames.

• Different from single image restoration, video restoration generally requires to utilize temporal information from multiple adjacent but usually misaligned video frames.
• Existing deep methods generally tackle with this by exploiting a sliding window strategy or a recurrent architecture, which either is restricted by frame-by-frame restoration or lacks long-range modelling ability.
• In this paper, we propose a Video Restoration Transformer (VRT) with parallel frame prediction and long-range temporal dependency modelling abilities.