Unsupervised Person Re-Identification
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Benchmarks
Market-1501
DukeMTMC-reID
MSMT17
DukeMTMC-reID->MSMT17
Market-1501->MSMT17
MSMT17->DukeMTMC-reID
MSMT17->Market-1501
DukeMTMC-VideoReID
DukeMTMCreID
ClonedPerson
LTCC
MARS
PRCC
PRID2011
PersonX
VC-Clothes
iLIDS-VID
Most implemented
Joint Discriminative and Generative Learning for Person Re-identification
Cluster Contrast for Unsupervised Person Re-Identification
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
Papers
A review of Recent Techniques for Person Re-Identification
Person re-identification (ReId), a crucial task in surveillance, involves matching individuals across different camera views. The advent of Deep Learning, especially supervised techniques like Convolutional Neural Networ…
Unsupervised Person Re-IdentificationTCMM: Token Constraint and Multi-Scale Memory Bank of Contrastive Learning for Unsupervised Person Re-identification
This paper proposes the ViT Token Constraint and Multi-scale Memory bank (TCMM) method to address the patch noises and feature inconsistency in unsupervised person re-identification works. Many excellent methods use ViT …
Contrastive LearningPerson Re-IdentificationPseudo LabelUnsupervised Person Re-IdentificationAnti-Forgetting Adaptation for Unsupervised Person Re-identification
Regular unsupervised domain adaptive person re-identification (ReID) focuses on adapting a model from a source domain to a fixed target domain. However, an adapted ReID model can hardly retain previously-acquired knowled…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationUnsupervised Person Re-IdentificationPose-Transformation and Radial Distance Clustering for Unsupervised Person Re-identification
Person re-identification (re-ID) aims to tackle the problem of matching identities across non-overlapping cameras. Supervised approaches require identity information that may be difficult to obtain and are inherently bia…
ClusteringPerson Re-IdentificationUnsupervised Person Re-Identification3C: Confidence-Guided Clustering and Contrastive Learning for Unsupervised Person Re-Identification
Unsupervised person re-identification (Re-ID) aims to learn a feature network with cross-camera retrieval capability in unlabelled datasets. Although the pseudo-label based methods have achieved great progress in Re-ID, …
ClusteringContrastive LearningPerson Re-IdentificationPseudo Label+1CORE-ReID: Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-Identification
This study introduces a novel framework, “Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-identification (CORE-ReID)”, to address an Unsupervised Domain Adaptation (UD…
Domain AdaptationPerson Re-IdentificationUnsupervised Domain AdaptationUnsupervised Person Re-Identification