[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.
The Official Implementation for "HAIR: Hypernetworks-based All-in-One Image Restoration".
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
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.
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"
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