[CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

[ACCV22] Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal, https://arxiv.org/abs/2210.03061

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

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

a dehaze / picture enhancement demo using ncnn

[Preprint] "Improved Techniques for Learning to Dehaze and Beyond: A Collective Study"

NTIRE 2020 NonHomogeneous Dehazing Challenge (CVPR Workshop 2020) 1st Solution.

A Python2 implementation of single image haze removal

A low-level vision zoo for dehazing, deblurring, denoising, deraining, inpainting, color enhancement, brightening, and super resolution .

Single Image Dehazing with a Generic Model-Agnostic Convolutional Neural Network

Transfer DeBlurGan to dehaze

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.

The Final Project of team 8, NTUEE, Digital Circuits Lab (2021 Fall)

Dark Channel Prior Based Image Dehazing Method

NeurIPS 2021 paper: Learning to Dehaze with Polarization

A cross-platform image dehazing/defogging mobile app implemented with React Native, Djinni and OpenCV, based on dark channel prior and fast guided filter.

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

Dataset and code of our AAAI2022 paper "Transmission-Guided Bayesian Generative Model for Smoke Segmentation"

Radiance-Reflectance Combined Optimization and Structure-Guided L0-Norm for Single Image Dehazing