Transformer for low-level vision applications, such as image restoration (denosing, super resolution, deblur)

• [Peking University] Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, Wen Gao: Pre-Trained Image Processing Transformer. [paper][code]
• [ETH Zurich] Jingyun Liang Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, Radu Timofte: SwinIR: Image Restoration Using Swin Transformer. [paper][code]
• [Peking University] Zhisheng Lu, Hong Liu, Juncheng Li, Linlin Zhang: Efficient Transformer for Single Image Super-Resolution. [paper]
• [USTC] Zhendong Wang, Xiaodong Cun, Jianmin Bao, Jianzhuang Liu: Uformer: A General U-Shaped Transformer for Image Restoration. [paper][code]
• [National University of Defense Technology] Zhengyu Liang, Yingqian Wang, Longguang Wang, Jungang Yang, Shilin Zhou: Light Field Image Super-Resolution with Transformers. [paper][code]
• [Wuhan Institute of Technology] Yuanzhi Wang, Tao Lu, Yanduo Zhang, Junjun Jiang, Jiaming Wang, Zhongyuan Wang, Jiayi Ma: TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network. [paper]
• [UESTC] Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng: Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution. [paper]
• [USTB] Chao Yao; Shuaiyong Zhang; Mengyao Yang; Meiqin Liu; Junpeng Qi: Depth Super-Resolution by Texture-Depth Transformer. [paper]
• [University of Massachusetts Lowell] Dayang Wang, Zhan Wu, Hengyong Yu:TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising. [paper]
• [Inception Institute of AI] Syed Waqas Zamir, Aditya Arora1 Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang: Restormer: Efficient Transformer for High-Resolution Image Restoration. [paper]
• [None] Haobo Ji, Xin feng, Wenjie Pei, Jinxing Li, Guangming Lu: U2-Former: A Nested U-shaped Transformer for Image Restoration. [paper]

• [ETH Zurich] Jiezhang Cao, Yawei Li, Kai Zhang, Luc Van Gool: Video Super-Resolution Transformer. [paper][code]

• [Nanjing University] Ming Lu, Peiyao Guo, Huiqing Shi, Chuntong Cao and Zhan Ma: Transformer-based Image Compression. [paper]