[CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors
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Updated
Jun 2, 2023 - Python
[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 Python2 implementation of single image haze removal
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
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"
A python package of robust and effective defogging/dehazing method
Lightweight and Efficient Image Dehazing Network Guided by Transmission Estimation from Real-world Hazy Scenes; accepted by Sensors 2021, 21(3), 960, MDPI; https://doi.org/10.3390/s21030960
This is an python implementation of "single image haze removal using dark channel prior"
实现了图片处理功能的平台,完成了数据库的持久化存储
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