SOTAVerified

Person Re-Identification

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.

Papers

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Showing 601–650 of 1488 papers

TitleStatusHype
Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification—0
Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification—0
Exploring Invariant Representation for Visible-Infrared Person Re-Identification—0
Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network—0
Confidence-guided Centroids for Unsupervised Person Re-Identification—0
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning—0
Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification—0
Compact Network Training for Person ReID—0
Exploiting Transitivity for Learning Person Re-Identification Models on a Budget—0
Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person Re-identification—0
Exploiting feature representations through similarity learning, post-ranking and ranking aggregation for person re-identification—0
Combining Two Adversarial Attacks Against Person Re-Identification Systems—0
Exciting-Inhibition Network for Person Reidentification in Internet of Things—0
Evolution of ReID: From Early Methods to LLM Integration—0
Event-Guided Person Re-Identification via Sparse-Dense Complementary Learning—0
Event-based Video Person Re-identification via Cross-Modality and Temporal Collaboration—0
Colors See Colors Ignore: Clothes Changing ReID with Color Disentanglement (ICCV-25 🥳)—0
Attention Driven Person Re-identification—0
Aligned Divergent Pathways for Omni-Domain Generalized Person Re-Identification—0
ESA-ReID: Entropy-Based Semantic Feature Alignment for Person re-ID—0
Ensemble Feature for Person Re-Identification—0
Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification—0
Enhancing Visible-Infrared Person Re-identification with Modality- and Instance-aware Visual Prompt Learning—0
Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person Re-Identification—0
Enhancing Person Re-Identification through Tensor Feature Fusion—0
Collaborative Attention Network for Person Re-identification—0
Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification—0
Enhancing Long-Term Person Re-Identification Using Global, Local Body Part, and Head Streams—0
Enhanced Visual-Semantic Interaction with Tailored Prompts for Pedestrian Attribute Recognition—0
COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification—0
Energy Clustering for Unsupervised Person Re-identification—0
End-to-End Training of CNN Ensembles for Person Re-Identification—0
Coarse-To-Fine Person Re-Identification With Auxiliary-Domain Classification and Second-Order Information Bottleneck—0
End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification—0
Coarse Attribute Prediction with Task Agnostic Distillation for Real World Clothes Changing ReID—0
Attention-based Shape and Gait Representations Learning for Video-based Cloth-Changing Person Re-Identification—0
Attention-based Few-Shot Person Re-identification Using Meta Learning—0
End-to-End Context-Aided Unicity Matching for Person Re-identification—0
End-to-End Comparative Attention Networks for Person Re-identification—0
CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification—0
Embedding Deep Metric for Person Re-identication A Study Against Large Variations—0
Embedding and Enriching Explicit Semantics for Visible-Infrared Person Re-Identification—0
Attention-Aware Compositional Network for Person Re-identification—0
Eliminating Background-Bias for Robust Person Re-Identification—0
EgoReID Dataset: Person Re-identification in Videos Acquired by Mobile Devices with First-Person Point-of-View—0
EgoReID: Cross-view Self-Identification and Human Re-identification in Egocentric and Surveillance Videos—0
Efficient PSD Constrained Asymmetric Metric Learning for Person Re-Identification—0
Cluster Loss for Person Re-Identification—0
Attention: A Big Surprise for Cross-Domain Person Re-Identification—0
Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification—0
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All datasetsMarket-1501DukeMTMC-reIDMSMT17Occluded-DukeMTMCMarket-1501-CCUHK03 detectedCUHK03 labeledMARSCUHK03LTCCPRCCPRID2011

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1st-ReID(RE, RK)Rank-198—Unverified
2SSKD(GH)Rank-197.36—Unverified
3CLIP-ReID+Pose2ID (no RK)Rank-197.3—Unverified
4SOLIDER +UFFM+AMCRank-197—Unverified
5Unsupervised Pre-training (ResNet101+MGN)Rank-197—Unverified
6RGT&RGPR (RK)Rank-196.9—Unverified
7SOLIDERRank-196.9—Unverified
8LightMBN (RR)Rank-196.8—Unverified
9Viewpoint-Aware Loss(RK)Rank-196.79—Unverified
10SOLIDER (RK)Rank-196.7—Unverified
#ModelMetricClaimedVerifiedStatus
1DenseILmAP97.1—Unverified
2CTL Model (ResNet50, 256x128)mAP96.1—Unverified
3BPBreID (RK)mAP92.9—Unverified
4Unsupervised Pre-training (ResNet101+RK)mAP92.77—Unverified
5st-ReID(RE, RK,Cam)mAP92.7—Unverified
6RGT&RGPR (RK)mAP92.7—Unverified
7Viewpoint-Aware Loss(RK)mAP91.8—Unverified
8LDS (ResNet50 + RK)mAP91—Unverified
9Adaptive L2 Regularization (with re-ranking)mAP90.7—Unverified
10FlipReID (with re-ranking)mAP90.7—Unverified