AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation

时间 2021-01-04

标签单目深度估计 adversarial domain adaptation cvpr2018 栏目 HTML 繁體版

原文原文链接

源码：https://www.iisc.ac.in/adadepth/ 源码很乱，看不懂，而且比较关键的部分都没有给。这篇文章看了很久，结合别的文章理解之后再读这篇文章，有了比较深的体会。重点：To generalize the learned features for the new domain, we plan to match the latent distributions of M

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1. Re-weighted adversarial adaptation network for unsupervised domain adaptation
2. Unsupervised Adversarial Depth Estimation using Cycled Generative Networks（2018.7）
3. 11.Unsupervised Monocular Depth Estimation with Left-Right Consistency
4. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
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6. 10.Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue
7. [cvpr2017]Deep Hashing Network for Unsupervised Domain Adaptation
8. Domain Adaptation for Object Recognition: An Unsupervised Approach
9. CVPR2019 Transferrable Prototypical Networks for Unsupervised Domain Adaptation
10. [CVPR 2018]Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
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1. Re-weighted adversarial adaptation network for unsupervised domain adaptation
2. Unsupervised Adversarial Depth Estimation using Cycled Generative Networks（2018.7）
3. 11.Unsupervised Monocular Depth Estimation with Left-Right Consistency
4. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
5. Geodesic flow kernel for unsupervised domain adaptation
6. 10.Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue
7. [cvpr2017]Deep Hashing Network for Unsupervised Domain Adaptation
8. Domain Adaptation for Object Recognition: An Unsupervised Approach
9. CVPR2019 Transferrable Prototypical Networks for Unsupervised Domain Adaptation
10. [CVPR 2018]Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

>>更多相关文章<<