Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification-Reference-Cited by-同舟云学术

Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification

Published:2023-01 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Piano Luca¹,Pratticò Filippo Gabriele¹,Sebastian Russo Alessandro¹,Lanari Lorenzo¹,Morra Lia¹,Lamberti Fabrizio¹

Affiliation:

1. Politecnico di Torino,Department of Control and Computer Engineering,Torino,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030335.pdf?arnumber=10030335

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4. Person Transfer GAN to Bridge Domain Gap for Person Re-identification

5. Domain-adversarial training of neural networks;ganin;The Journal of Machine Learning Research,2016

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