Video deblur, super-resolution, and denoise using transformer with VRT
Video deblur, super-resolution, and denoise using transformer with VRT
VRT: A Video Restoration Transformer
arXiv paper abstract https://arxiv.org/abs/2201.12288
arXiv PDF paper https://arxiv.org/pdf/2201.12288.pdf
GitHub https://github.com/JingyunLiang/VRT
Video restoration (e.g., video super-resolution) aims to restore high-quality frames from low-quality frames.
… Existing … methods … exploiting a sliding window strategy or a recurrent architecture, which … is restricted by frame-by-frame restoration or lacks long-range modelling ability.
… propose a Video Restoration Transformer (VRT) with parallel frame prediction and long-range temporal dependency modelling abilities.
… VRT is composed of multiple scales … consists of … temporal mutual self attention (TMSA) and parallel warping.
TMSA divides the video into small clips, on which mutual attention is applied for joint motion estimation, feature alignment and feature fusion, while self attention is used for feature extraction.
… Experimental … on … video super-resolution, video deblurring and video denoising, demonstrate that VRT outperforms the state-of-the-art methods by large margins (up to 2.16dB) on nine benchmark datasets.
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