Bidirectional Learning for Domain Adaptation of Semantic Segmentation详读
Bidirectional Learning for Domain Adaptation of Semantic Segmentation 简介 具体方法 简介 语义分割在深度网络的驱使下发展迅速，但是大规模的数据标注太过昂贵。虽然，近期的工作可以通过生成式网络使计算机生成带标注的比较逼真的图像，但是这种方式生成的图像存在域不匹配的问题，即计算机生成的图像（源域）和测试时使用的图像（目标域）之间的
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相关文章
- 1. Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation
- 2. Fully Convolutional Adaptation Networks for Semantic Segmentation
- 3. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 4. Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
- 5. 论文阅读 | A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
- 6. 论文阅读：Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
- 7. 读论文《SSF-DAN: Separated Semantic Feature based Domain Adaptation Network for Semantic Segmentation》记录
- 8. Review of Semantic Segmentation with Deep Learning
- 9. 《Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision》论文笔记
- 10. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation