perseveranceLX's repositories
UIE-UIR__TPAMI-IJCV-TIP
Underwater image enhancement/restoration methods in TPAMI/IJCV/TIP .
IQA-PyTorch
PyTorch Toolbox for Image Quality Assessment, including MUSIQ, NIMA, LPIPS, DBCNN, WaDIQaM, NRQM(Ma), BRISQUE, NIQE, PI and more...
iterative-dehaze
Progressive Update Guided Interdependent Networks for Single Image Dehazing
BDLFusion
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond (IJCAI 23)
CMFNet
Compound Multi-branch Feature Fusion for Real Image Restoration
CODE-Net
Single Image Deraining with Coutinuous Density Estimation
DCSR
[ICCV 2021 (Oral Presentation)] Dual-Camera Super-Resolution with Aligned Attention Modules (RefSR)
Diffusion-Super-Resolution
[CVPR 2023] Guided Depth Super-Resolution by Deep Anisotropic Diffusion
Diffusion4SR
Super Resolution Utilizing the Denoising Diffusion Probabilistic Models
EnlightenGAN
[IEEE TIP'2021] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
ICCV2021-Single-Image-Desnowing-HDCWNet
This paper is accepted by ICCV 2021.
InDI-implementation
Unofficial Pytorch implementation of the Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration (InDI)) by Delbracio et al 2023
Light-DehazeNet
Light-DehazeNet: A Novel Lightweight CNN Architecture for Single Image Dehazing
LPTN
Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021
LRT-HDR
Python code and data for "Deep Unrolled Low-Rank Tensor Completion for High Dynamic Range Imaging"
MonoUIR
Implementation of "Towards Underwater Image Restoration: A Physical-accurate Pipeline and a Large Scale Full-reference Benchmark, International Conference on Multimedia and Expo(ICME), 2022"
perseveranceLX.github.io
我的学术主页
SUNet
SUNet: Swin Transformer with UNet for Image Denoising
WACV2024-SAFA
WACV2024 - Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution