[CVPR 2022] Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model
-
Updated
Sep 3, 2022 - Python
[CVPR 2022] Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model
Pytorch Code for the paper TransWeather - CVPR 2022
Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN). ECCV, 2022.
This is the source code of PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal which has been accepted by IEEE Transaction on Image Processing 2020.
Inference code for "Unified Multi-Weather Transformer for Multi-Weather Image Restoration".
Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]
This paper is accepted by IEEE TCSVT
[ICCV 2023] Snow Removal in Video: A New Dataset and A Novel Method
This paper is accepted by ICCV 2021.
This is the project page of our paper which has been published in ECCV 2020.
The official code of the IEEE Access paper Multiple Adverse Weather Removal Using Masked-Based Pre-Training and Dual-Pooling Adaptive Convolution (MPDAC)
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
[ECCV 2024] Histoformer: Restoring Images in Adverse Weather Conditions via Histogram Transformer
[ECCV 2024] OneRestore: A Universal Restoration Framework for Composite Degradation
Add a description, image, and links to the desnowing topic page so that developers can more easily learn about it.
To associate your repository with the desnowing topic, visit your repo's landing page and select "manage topics."