Deep learning training framework for image super resolution and restoration.
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Updated
Jun 29, 2024 - Python
Deep learning training framework for image super resolution and restoration.
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
Official implementation of the paper "DeblurDiNAT: A Lightweight and Effective Transformer for Image Deblurring".
[CVPR 2024] "CFAT: Unleashing Triangular Windows for Image Super-resolution"
A Collection of Papers and Codes for CVPR2024/CVPR2021/CVPR2020 Low Level Vision
About me
This is the source code of PMS-Net: Robust Haze Removal Based on Patch Map for Single Images which has been published in CVPR 2019 Long Beach
neosr is a framework for training real-world single-image super-resolution networks.
Revisiting Image Deblurring with an Efficient ConvNet - An efficient CNN performs better than Transformer
[ECCV 2022 & T-PAMI 2024] Multiple Look-Up Tables for Efficient Image Restoration
Learning Accurate and Enriched Features for Stereo Image Super-Resolution
Compound Multi-branch Feature Fusion for Real Image Restoration
This is the official PyTorch implementation of DehazeDCT. Our method achieves the second best performance in NTIRE 2024 Dense and NonHomogeneous Dehazing Challenge (CVPR workshop))
This is the official PyTorch implementation of ShadowRefiner. Our method is winner of Perceptual Track and achieves the second-best performance for Fidelity Track in NTIRE 2024 Shadow Removal Challenge (CVPR 2024 Workshop)
A Collection of Low Level Vision Research Groups
Awesome Remote Sensing Toolkit based on PaddlePaddle.
[Knowledge-Based Systems] Exploring the Potential of Channel Interactions for Image Restoration
"Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement" (ICCV 2023) & (NTIRE 2024 Challenge)
"MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction" (CVPRW 2022) & (Winner of NTIRE 2022 Spectral Recovery Challenge) and a toolbox for spectral reconstruction
A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.
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