【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(...
[CVPR 2020-图像去雾] Domain Adaptation for Image Dehazing 蓝色夜晚的记忆 3 人赞同了该文章 项目地址 | 论文地址 研究动机及贡献 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...
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 ...
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...
Specifically, a novel domain adaptation framework for real-world underwater image enhancement inspired by transfer learning is presented; it transfers in-air image dehazing to real-world underwater image enhancement. The experimental results on different real-world underwater scenes indicate that 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...
Shao Y, Li L, Ren W, Gao C, Sang N (2020) Domain adaptation for image dehazing. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 2808–2817 Yang C, Lim S-N (2020) One-shot domain adaptation for face generation. In: Proceedings of the IEEE/...
Dong Y, Li Y, Dong Q, Zhang H, Chen S (2022) Semi-supervised domain alignment learning for single image dehazing. IEEE Trans Cybern Ghifary M, Kleijn WB, Zhang M, Balduzzi D, Li W (2016) Deep reconstruction-classification networks for unsupervised domain adaptation. In: Computer vision–EC...
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...
Deep learning-based source dehazing methods trained on synthetic datasets have achieved remarkable performance but suffer from dramatic performance degradation on real hazy images due to domain shift. Although certain Domain Adaptation (DA) dehazing methods have been presented, they inevitably require ...