Person Re-Identification
510 papers with code • 34 benchmarks • 57 datasets
Person Re-Identification is a computer vision task in which the goal is to match a person's identity across different cameras or locations in a video or image sequence. It involves detecting and tracking a person and then using features such as appearance, body shape, and clothing to match their identity in different frames. The goal is to associate the same person across multiple non-overlapping camera views in a robust and efficient manner.
Benchmarks
These leaderboards are used to track progress in Person Re-Identification
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Libraries
Use these libraries to find Person Re-Identification models and implementations
Market-1501
CUHK03
DukeMTMC-reID
MARS
VIPeR
CUHK-SYSU
SYSU-MM01
PRW
Occluded REID
Subtasks
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Unsupervised Person Re-Identification
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Video-Based Person Re-Identification
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Generalizable Person Re-identification
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Cloth-Changing Person Re-Identification
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Cloth-Changing Person Re-Identification
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Large-Scale Person Re-Identification
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Cross-Modal Person Re-Identification
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Self-Supervised Person Re-Identification
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Clothes Changing Person Re-Identification
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Image-To-Video Person Re-Identification
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Semi-Supervised Person Re-Identification
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Direct Transfer Person Re-identification
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Federated Lifelong Person ReID
Latest papers
A Survey on 3D Skeleton Based Person Re-Identification: Approaches, Designs, Challenges, and Future Directions
Person re-identification via 3D skeletons is an important emerging research area that triggers great interest in the pattern recognition community.
Image-based human re-identification: Which covariates are actually (the most) important?
KaiyangZhou/deep-person-reid
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Image and Vision Computing 2024
Human re-identification (re-ID) is nowadays among the most popular topics in computer vision, due to the increasing importance given to safety/security in modern societies.
Exploring Color Invariance through Image-Level Ensemble Learning
This issue is particularly pronounced in complex wide-area surveillance scenarios, such as person re-identification and industrial dust segmentation, where models often experience a decline in performance due to overfitting on color information during training, given the presence of environmental variations.
CPCL: Cross-Modal Prototypical Contrastive Learning for Weakly Supervised Text-based Person Re-Identification
Weakly supervised text-based person re-identification (TPRe-ID) seeks to retrieve images of a target person using textual descriptions, without relying on identity annotations and is more challenging and practical.
Mutual Distillation Learning For Person Re-Identification
kuilongcui/mdpr
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With the rapid advancements in deep learning technologies, person re-identification (ReID) has witnessed remarkable performance improvements.
Masked Attribute Description Embedding for Cloth-Changing Person Re-identification
moon-wh/made
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To address this, we mask the clothing and color information in the personal attribute description extracted through an attribute detection model.
AG-ReID.v2: Bridging Aerial and Ground Views for Person Re-identification
To address this, we introduce AG-ReID. v2, a dataset specifically designed for person Re-ID in mixed aerial and ground scenarios.
Temporal 3D Shape Modeling for Video-Based Cloth-Changing Person Re-Identification
dustin-nguyen-qil/Videobased-ClothChanging-ReID-Baseline
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IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops 2024
In this work, we propose "Temporal 3D ShapE Modeling for VCCRe-ID" (SEMI), a lightweight end-to-end framework that addresses these issues by learning human 3D shape representations.
Contrastive Viewpoint-aware Shape Learning for Long-term Person Re-Identification
jurgendn/CVSL_LReID
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IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2024
In this paper, we propose "Contrastive Viewpoint-aware Shape Learning for Long-term Person Re-Identification" (CVSL) to address these challenges.
TF-CLIP: Learning Text-free CLIP for Video-based Person Re-Identification
Technically, TMC allows the frame-level memories in a sequence to communicate with each other, and to extract temporal information based on the relations within the sequence.
