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
Camera Alignment and Weighted Contrastive Learning for Domain Adaptation in Video Person ReIDCode0
Generalizable Re-Identification from Videos with Cycle Association—0
Sequential Transformer for End-to-End Person Search—0
Deep Multimodal Fusion for Generalizable Person Re-identificationCode0
PhysioGait: Context-Aware Physiological Context Modeling for Person Re-identification Attack on Wearable Sensing—0
Unsupervised domain-adaptive person re-identification with multi-camera constraints—0
Adaptive Cross-Domain Learning for Generalizable Person Re-Identification—0
End-to-End Context-Aided Unicity Matching for Person Re-identification—0
Domain generalization Person Re-identification on Attention-aware multi-operation strategery—0
Handling Label Uncertainty for Camera Incremental Person Re-Identification—0
Pyramidal Transformer with Conv-Patchify for Person Re-identificationCode0
Specialized Re-Ranking: A Novel Retrieval-Verification Framework for Cloth Changing Person Re-Identification—0
Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification—0
How Image Generation Helps Visible-to-Infrared Person Re-Identification?—0
FRIDA: Fisheye Re-Identification Dataset with Annotations—0
Robust Person Identification: A WiFi Vision-based Approach—0
Pose-Aided Video-based Person Re-Identification via Recurrent Graph Convolutional Network—0
Grouped Adaptive Loss Weighting for Person Search—0
Multi-Granularity Graph Pooling for Video-based Person Re-Identification—0
TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly DetectionCode0
Is Synthetic Dataset Reliable for Benchmarking Generalizable Person Re-Identification?—0
Style Variable and Irrelevant Learning for Generalizable Person Re-identificationCode0
Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images—0
Skeleton Prototype Contrastive Learning with Multi-Level Graph Relation Modeling for Unsupervised Person Re-IdentificationCode0
Identity-Sensitive Knowledge Propagation for Cloth-Changing Person Re-identificationCode0
Dynamic Template Initialization for Part-Aware Person Re-ID—0
CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification—0
Synthetic Data in Human Analysis: A Survey—0
Domain Camera Adaptation and Collaborative Multiple Feature Clustering for Unsupervised Person Re-ID—0
Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification—0
Deep Learning-based Occluded Person Re-identification: A Survey—0
Look Closer to Your Enemy: Learning to Attack via Teacher-Student MimickingCode0
Portrait Interpretation and a Benchmark—0
A Semantic-aware Attention and Visual Shielding Network for Cloth-changing Person Re-identification—0
Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars—0
Towards Privacy-Preserving Person Re-identification via Person Identify Shift—0
Rapid Person Re-Identification via Sub-space Consistency Regularization—0
Dynamic Gradient Reactivation for Backward Compatible Person Re-identification—0
Learning Resolution-Adaptive Representations for Cross-Resolution Person Re-Identification—0
Pseudo-Pair based Self-Similarity Learning for Unsupervised Person Re-identification—0
Style Interleaved Learning for Generalizable Person Re-identificationCode0
Context Sensing Attention Network for Video-based Person Re-identification—0
Unsupervised Learning for Human Sensing Using Radio Signals—0
Adversarial Pairwise Reverse Attention for Camera Performance Imbalance in Person Re-identification: New Dataset and Metrics—0
Learning Towards the Largest Margins—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Towards Generalizable Person Re-identification with a Bi-stream Generative Model—0
Plug-and-Play Pseudo Label Correction Network for Unsupervised Person Re-identification—0
Cross-modal Local Shortest Path and Global Enhancement for Visible-Thermal Person Re-Identification—0
Feature-Distribution Perturbation and Calibration for Generalized Person ReID—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