[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
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Aug 16, 2024 - Python
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
[CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.
A Collection of Papers and Codes for CVPR2024/CVPR2021/CVPR2020 Low Level Vision
[CVPR 2022] Official implementation of the paper "Uformer: A General U-Shaped Transformer for Image Restoration".
[ICLR 2024] Controlling Vision-Language Models for Universal Image Restoration. 5th place in the NTIRE 2024 Restore Any Image Model in the Wild Challenge.
PromptIR: Prompting for All-in-One Blind Image Restoration [NeurIPS 2023]
A Flexible and Unified Image Restoration Framework (PyTorch), including state-of-the-art image restoration model. Such as NAFNet, Restormer, MPRNet, MIMO-UNet, SCUNet, SwinIR, HINet, etc. ⭐⭐⭐⭐⭐⭐
A Collection of Papers and Codes for ECCV2024/ECCV2020 Low Level Vision
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
KBNet: Kernel Basis Network for Image Restoration
A Collection of Low Level Vision Research Groups
[ECCV 2024] Histoformer: Restoring Images in Adverse Weather Conditions via Histogram Transformer
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
[ICLR 2023] Selective Frequency Network for Image Restoration
ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration
Compound Multi-branch Feature Fusion for Real Image Restoration
Revitalizing Convolutional Network for Image Restoration
[TPAMI] Image Restoration via Frequency Selection
Official repository for the paper "Image Deraining Transformer".
[Knowledge-Based Systems] Exploring the Potential of Channel Interactions for Image Restoration
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