域自适应相关论文

刚刚接触域自适应方向，相关论文和代码如下：
1.Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image Segmentation. https://github.com/sulaimanvesal/PointCloudUDA
2 DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation. https://github.com/lhoyer/DAFormer
3.Dual Path Learning for Domain Adaptation of Semantic Segmentation. https://github.com/royee182/DPL
4 .DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training. https://github.com/yufei1900/DAST segmentation
5.Self-supervised Augmentation Consistency for Adapting Semantic Segmentation. https://github.com/visinf/da-sac
6.Bidirectional Learning for Domain Adaptation of Semantic Segmentation. https://github.com/liyunsheng13/BDL
7.基于对抗学习的医学图像分割领域自适应研究
8.HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation. https://github.com/lhoyer/hrda
域自适应目前主要还是应用在医学和驾驶两个方向。方法大都是判别器、自监督和图像翻译相结合，22年以前以卷积为主，22年出了两篇transformer得域自适应相关论文 (DAFormer, HRDA)。以后得论文可能还得是transformer，毕竟万物都可tran。