The state-of-the-art image restoration model without nonlinear activation functions.
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Updated
Apr 22, 2024 - Python
The state-of-the-art image restoration model without nonlinear activation functions.
[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.
[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.
Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
Simple framework for image and video deblurring, implemented by PyTorch
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. ⭐⭐⭐⭐⭐⭐
[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark
KBNet: Kernel Basis Network for Image Restoration
This is a survey that reviews deep learning models and benchmark datasets related to blind motion deblurring and provides a comprehensive evaluation of these models.
Code for paper: Memory Augment is All Your Need for image restoration(cloud,rain,shadow removal, low-light image enhancement, image deblur)即插即用提点的记忆模块
Compound Multi-branch Feature Fusion for Real Image Restoration
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
Revisiting Image Deblurring with an Efficient ConvNet - An efficient CNN performs better than Transformer
Image deblurring with Convolutional Neural Networks. Scripts & Neural network models available here
Tensorflow implementation of MemNet(http://cvlab.cse.msu.edu/pdfs/Image_Restoration%20using_Persistent_Memory_Network.pdf).
[Knowledge-Based Systems] Exploring the Potential of Channel Interactions for Image Restoration
[TPAMI] Image Restoration via Frequency Selection
deep learning models trained to denoise/deblur text images (signle frame, multi-frame) [pytorch]
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