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Found 6 papers, 4 papers with code
Learning Feature Fusion for Unsupervised Domain Adaptive Person Re-identification
Unsupervised domain adaptive (UDA) person re-identification (ReID) has gained increasing attention for its effectiveness on the target domain without manual annotations.
Ranked #1 on
Unsupervised Domain Adaptation
on Market to Duke
Unsupervised Domain Adaptation
Unsupervised Domain Adaptationn
+2
One More Check: Making "Fake Background" Be Tracked Again
Eventually, it helps to reload the ``fake background'' and repair the broken tracklets.
Rethinking the competition between detection and ReID in Multi-Object Tracking
However, the inherent differences and relations between detection and re-identification (ReID) are unconsciously overlooked because of treating them as two isolated tasks in the one-shot tracking paradigm.
Ranked #1 on
Multi-Object Tracking
on HiEve
(using extra training data)
Adaptive Graph Representation Learning for Video Person Re-identification
While correlations between parts are ignored in the previous methods, to leverage the relations of different parts, we propose an innovative adaptive graph representation learning scheme for video person Re-ID, which enables the contextual interactions between relevant regional features.
Ranked #3 on
Person Re-Identification
on PRID2011
Graph Representation Learning
Video-Based Person Re-Identification
