A DIRT-T APPROACH TO UNSUPERVISED DOMAIN ADAPTATION
这篇是一篇领域自适应（domain adaption，迁移学习的一种）方面的文章，因为我本身的研究方向不是这个，只是老师推荐看的所以我就随便做点笔记，就当做整理一下自己的思路吧。说实话，这里肯定有很多专业术语上面的问题或者其他方面的问题，麻烦大家多多包涵啦。 基本问题和动机： 领域自适应（Domain adaptation）是指利用源域（source domain）中的标记数据来学习一个可以应用于
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相关文章
- 1. Domain Adaptation for Object Recognition: An Unsupervised Approach
- 2. Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-ID
- 3. Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-id
- 4. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 5. Geodesic flow kernel for unsupervised domain adaptation
- 6. 论文阅读 | A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
- 7. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 8. [MICCAI2019]Unsupervised Domain Adaptation via Disentangled Representations
- 9. Unsupervised Domain Adaptation by Backpropagation(2015)
- 10. [cvpr2017]Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks