Unsupervised Person Re-Identification
58 papers with code • 19 benchmarks • 11 datasets
Benchmarks
These leaderboards are used to track progress in Unsupervised Person Re-Identification
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Datasets
Market-1501
DukeMTMC-reID
MSMT17
MARS
DukeMTMC-VideoReID
iLIDS-VID
Latest papers
Camera-aware Label Refinement for Unsupervised Person Re-identification
leeboomla/calr
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Unsupervised person re-identification aims to retrieve images of a specified person without identity labels.
Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification
RikoLi/PCL-CLIP
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Although prompt learning has enabled a recent work named CLIP-ReID to achieve promising performance, the underlying mechanisms and the necessity of prompt learning remain unclear due to the absence of semantic labels in ReID tasks.
Hierarchical Skeleton Meta-Prototype Contrastive Learning with Hard Skeleton Mining for Unsupervised Person Re-Identification
kali-hac/hi-mpc
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Then a hierarchical meta-prototype contrastive learning model is proposed to cluster and contrast the most typical skeleton features ("prototypes") from different-level skeletons.
SiCL: Silhouette-Driven Contrastive Learning for Unsupervised Person Re-Identification with Clothes Change
In this paper, we address a highly challenging yet critical task: unsupervised long-term person re-identification with clothes change.
Learning Transferable Pedestrian Representation from Multimodal Information Supervision
Recent researches on unsupervised person re-identification~(reID) have demonstrated that pre-training on unlabeled person images achieves superior performance on downstream reID tasks than pre-training on ImageNet.
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identification
theziqi/dccc
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To address this problem, we propose a dynamic clustering and cluster contrastive learning (DCCC) method.
Learning Invariance from Generated Variance for Unsupervised Person Re-identification
This work focuses on unsupervised representation learning in person re-identification (ReID).
Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
rikoli/wacv23-workshop-tmgf
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To this end, we build a dual-branch network architecture based upon a modified Vision Transformer (ViT).
Skeleton Prototype Contrastive Learning with Multi-Level Graph Relation Modeling for Unsupervised Person Re-Identification
kali-hac/spc-mgr
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Lastly, we propose a skeleton prototype contrastive learning scheme that clusters feature-correlative instances of unlabeled graph representations and contrasts their inherent similarity with representative skeleton features ("skeleton prototypes") to learn discriminative skeleton representations for person re-ID.
A High-Accuracy Unsupervised Person Re-identification Method Using Auxiliary Information Mined from Datasets
Combined with auxiliary information exploiting modules, our methods achieve mAP of 89. 9% on DukeMTMC, where TOC, STS and SCP all contributed considerable performance improvements.
