【论文翻译】DA_dahazing: Domain Adaptation for Image Dehazing 摘要 近年来,使用基于学习的方法进行图像去雾已经达到了最先进的性能。 然而,大多数现有方法在合成模糊图像上训练去雾模型,由于域迁移(domain shift),这些模型面对真实的模糊图像泛化(generalize)能力不强。为了解决这个问题,我们提出了一种领域适应范式(...
基于学习的图像去雾算法在合成数据上取得了很好地性能,但是由于存在域鸿沟导致基于学习的去雾模型很难处理真实的有雾图像。为了解决该问题,本文提出域自适应范式,其中包含一个图像转换模块和两个图像去雾模块。双向图像转换模块旨在弥合合成域与真实域之间的差距,使用转换前后的图像借助一致性损失来训练去雾模块。在训练...
Domain Adaptation for Image Dehazing 来自 钛学术 喜欢 0 阅读量: 776 公开/公告号: 10.1109/CVPR42600.2020.00288 公开/公告日期: 05 August 2020 发明人:Y Shao,L Li,W Ren,C Gao,N Sang 摘要: Image dehazing using learning-based methods has achieved state-of-the-art performance in recent years....
Domain AdaptationGenerative Adversarial NetVariational AutoencoderDeep LearningMost existing image dehazing methods based learning are less able to perform well to real hazy images. An important reason is that they are trained on synthetic hazy images whose distribution is different from real hazy images...
Domain-adaptation-and-image-dehazing-on-nighttime-hazy-images Coursework project: Advanced Image Processing and Deep learning - UJM, France Project owners: Milan Kresovic, David Díaz Estrada, Thong Nguyen. This project is inspired from this paper and this project to implement a domain adaptation ...
When encountering the distribution shift between the source (training) and target (test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot
Domain Adaptation for Image Dehazing [CVPR2020] Probability Weighted Compact Feature for Domain Adaptive Retrieval [CVPR2020] [code] Disparity-Aware Domain Adaptation in Stereo Image Restoration [CVPR2020] Multi-Path Learning for Object Pose Estimation Across Domains [CVPR2020] Unsupervised Domain Adaptati...
Firstly, we introduce cross-attention as a fine-grained domain adaptation constraint into the CDAG-network, to enhance its capability in analyzing features from real and synthetic domains and aligning their distributions. Secondly, in light of the complex nature of rain artifacts, we propose the ...
Domain Adaptation for Image Dehazing [CVPR2020] Probability Weighted Compact Feature for Domain Adaptive Retrieval [CVPR2020] [code] Disparity-Aware Domain Adaptation in Stereo Image Restoration [CVPR2020] Multi-Path Learning for Object Pose Estimation Across Domains [CVPR2020] Unsupervised Domain Adaptati...
Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle Deep learning-based methods have made significant achievements for image dehazing. However, most of existing dehazing networks are concentrated on training models using simulated hazy images, resulting in genera...