Unsupervised Cross-Dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns

Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly deploying these trained models to a large-scale real-world camera network may lead to poor performance due to underfitting. It is challenging to in...

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Veröffentlicht in:2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition S. 7948 - 7956
Hauptverfasser: Lv, Jianming, Chen, Weihang, Li, Qing, Yang, Can
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2018
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ISSN:1063-6919
Online-Zugang:Volltext
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