Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]

Pytorch Code for the paper TransWeather - CVPR 2022

[CVPR 2022] Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model

[ECCV 2024] Histoformer: Restoring Images in Adverse Weather Conditions via Histogram Transformer

Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN). ECCV, 2022.

[ECCV 2024] OneRestore: A Universal Restoration Framework for Composite Degradation

This paper is accepted by ICCV 2021.

[ICCV 2023] Snow Removal in Video: A New Dataset and A Novel Method

[ NeurIPS 2024 ] The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration.

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.

This is the project page of our paper which has been published in ECCV 2020.

[ECCV‘24] Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraint

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

Towards Real-World Adverse Weather Image Restoration: Enhancing Clearness and Semantics with Vision-Language Models (ECCV 2024)

Inference code for "Unified Multi-Weather Transformer for Multi-Weather Image Restoration".

This paper is accepted by IEEE TCSVT

The official code of the IEEE Access paper "Multiple Adverse Weather Removal Using Masked-Based Pre-Training and Dual-Pooling Adaptive Convolution (MPDAC)"