Domain Adaptation Through Synthesis for Unsupervised Person Re-identification-Reference-Cited by-同舟云学术

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Domain Adaptation Through Synthesis for Unsupervised Person Re-identification

Published:2018 Issue: Volume: Page:193-209
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2018
language:
Short-container-title:

Author:

Bąk Sławomir^ORCID,Carr Peter,Lalonde Jean-François^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-01261-8_12

Reference52 articles.

1. Aharon, M., Elad, M., Bruckstein, A.: K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 54(11), 4311–4322 (2006)

2. Bak, S., Carr, P.: One-shot metric learning for person re-identification. In: CVPR, June 2017

3. Chen, W., Chen, X., Zhang, J., Huang, K.: Beyond triplet loss: a deep quadruplet network for person re-identification. In: CVPR, July 2017

4. Cheng, D., Gong, Y., Zhou, S., Wang, J., Zheng, N.: Person re-identification by multi-channel parts-based CNN with improved triplet loss function. In: CVPR, June 2016

5. Debevec, P.: Rendering synthetic objects into real scenes: bridging traditional and image-based graphics with global illumination and high dynamic range photography. In: Proceedings of ACM SIGGRAPH, pp. 189–198 (1998)

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