Unsupervised Visual Domain Adaptation:A Deep Max-Margin Gaussian Process Approach : Oral Paper at CVPR 2019

This is a joint work by Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic.

For more information please visit: “https://seqam-lab.github.io/GPDA

References

[1] M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019.

[Bibtex]

@InProceedings{Kim_2019_CVPR,
author = {Kim, Minyoung and Sahu, Pritish and Gholami, Behnam and Pavlovic, Vladimir},
title = {Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}

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