VRT: A Video Restoration Transformer
Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool
Computer Vision Lab, ETH Zurich & Meta Inc.
arxiv
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supplementary
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pretrained models
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visual results
This repository is the official PyTorch implementation of “VRT: A Video Restoration Transformer”
(arxiv, supp, pretrained models, visual results). VRT ahcieves state-of-the-art performance (up to 2.16dB) in
- video SR (REDS, Vimeo90K, Vid4 and UDM10)
- video deblurring (GoPro, DVD and REDS)
- video denoising (DAVIS and Set8)