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

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

16 April 2023
Luca Piano
F. G. Pratticó
Alessandro Sebastian Russo
Lorenzo Lanari
Lia Morra
Fabrizio Lamberti
ArXivPDFHTML

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

4 / 4 papers shown
Title
Efficient large-scale image retrieval with deep feature orthogonality
  and Hybrid-Swin-Transformers
Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers
Christof Henkel
25
14
0
07 Oct 2021
TransReID: Transformer-based Object Re-Identification
TransReID: Transformer-based Object Re-Identification
Shuting He
Haowen Luo
Pichao Wang
F. Wang
Hao Li
Wei Jiang
ViT
213
788
0
08 Feb 2021
Transformers in Vision: A Survey
Transformers in Vision: A Survey
Salman Khan
Muzammal Naseer
Munawar Hayat
Syed Waqas Zamir
F. Khan
M. Shah
ViT
225
2,427
0
04 Jan 2021
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
149
9,316
0
28 May 2015
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