luguoxinxin

luguoxinxin's Stars

• swz30/Restormer

  [CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.

  Language:Python1.8k18101234

• dawnlh/awesome-low-light-image-enhancement

  This is a resouce list for low light image enhancement

  Language:MATLAB1.4k3522211

• yulunzhang/RCAN

  PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

  Language:Python1.4k23129314

• JingyunLiang/VRT

  VRT: A Video Restoration Transformer (official repository)

  Language:Python1.4k1763130

• researchmm/TTSR

  [CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution

  Language:Python7651456115

• zhaohengyuan1/PAN

  (ECCV2020 Workshops) Efficient Image Super-Resolution Using Pixel Attention.

  Language:Python31881035

• ShuhangGu/DASR

  Training and Testing codes for our paper "Real-world Image Super-resolution via Domain-distance Aware Training"

  Language:Python23592221

• chaofengc/FeMaSR

  PyTorch codes for "Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors", ACM MM2022 (Oral)

  Language:Python20652416

• xindongzhang/ELAN

  [ECCV2022] Efficient Long-Range Attention Network for Image Super-resolution

  Language:Python20281917

• JingyunLiang/HCFlow

  Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)

  Language:Python188121428

• HarukiYqM/Non-Local-Sparse-Attention

  PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

  Language:Python17533320

• xiaom233/BSRN

  Blueprint Separable Residual Network for Efficient Image Super-Resolution

  Language:Python16861514

• greatlog/UnpairedSR

  This is an offical implementation of the CVPR2022's paper [Learning the Degradation Distribution for Blind Image Super-Resolution](https://arxiv.org/abs/2203.04962)

  Language:Python16244111

• chxy95/HDRUNet

  CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

  Language:Python15682228

• Algolzw/EBSR

  Pytorch code for "EBSR: Feature Enhanced Burst Super-Resolution with Deformable Alignment", CVPRW 2021, 1st NTIRE (real data track).

  Language:Python9451411

• sunny2109/MobileSR-NTIRE2022

  [NTIRE 2022, EfficientSR] MobileSR: A Mobile-friendly Transformer for Efficient Image Super-Resolution

  Language:Python69488

• Zj-BinXia/AMSA

  This project is the official implementation of 'Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution', AAAI2022

  Language:Python692135

• icandle/EFDN

  Edge-enhanced Feature Distillation Network for Efficient Super-Resolution (CVPRW 2022)

  Language:Python63194

• codyshen0000/ITSRN

  Code repo for "Implicit Transformer Network for Screen ContentImage Continuous Super-Resolution" (NeurIPS'21)

  Language:Python49997

• AlexZou14/SCET

  Self-Calibrated Efficient Transformer for Lightweight Super-Resolution (offical)

  Language:Python37367

• researchmm/CyDAS

  Cyclic Differentiable Architecture Search

  Language:Python35526

• lusinlu/gradient-variance-loss

  Code of the ICASSP 2022 paper "Gradient Variance Loss for Structure Enhanced Super-Resolution"

  Language:Python27130

• sunsmarterjie/GOLD_NAS

  The implementation of GOLD_NAS

  Language:Python23241

• DawnHH/DLSR-PyTorch

  This repository is an implementation of the paper "Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Search".

  Language:Python22211

• kalpeshjp89/USISResNet

  This repository includes code of training/testing of our work published in NTIRE-2020 workshop titled "Unsupervised Single Image Super-Resolution Network (USISResNet) for Real-World Data Using Generative Adversarial Network".

  Language:Python16197

• VITA-Group/CERL

  [Preprint] "CERL: Coordinated Enhancement for Real-World Low-Light Noisy Images" by Zeyuan Chen, Yifan Jiang, Dong Liu and Zhangyang Wang

  Language:Python14844

• kalpeshjp89/DUSGAN

  Official code of "Direct Unsupervised Super-Resolution using Generative Adversarial Network (DUS-GAN) for Real-World Data" published in an IEEE Transaction in Image Processing (TIP).

  Language:Python6121

• BasavarajMS11/Under-Water-Image-Super-Resolution

  Deep learning model for a given underwater low-resolution degraded image, that enhance the image to remove degradation effects and later improve the quality of image by super resolution.

  Language:Python52

• callous-youth/BETAK

  Code for paper named "Advancing Generalized Transfer Attack with Initialization Derived Bilevel Optimization and Dynamic Sequence Truncation""

  Language:Python10

• jqsun98/machinelearning

  My blogs and code for machine learning. http://cnblogs.com/pinard

  Language:Jupyter Notebook1100