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 1451–1488 of 1488 papers

TitleStatusHype
Multiple Integration Model for Single-source Domain Generalizable Person Re-identification—0
Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification—0
Multiple People Tracking by Lifted Multicut and Person Re-Identification—0
Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification—0
Multi-Prompts Learning with Cross-Modal Alignment for Attribute-based Person Re-Identification—0
Multi-pseudo Regularized Label for Generated Data in Person Re-Identification—0
Multi-Resolution Overlapping Stripes Network for Person Re-Identification—0
Multi-scale 3D Convolution Network for Video Based Person Re-Identification—0
Multi-Scale Body-Part Mask Guided Attention for Person Re-identification—0
Multi-Scale Cascading Network with Compact Feature Learning for RGB-Infrared Person Re-Identification—0
Multi-scale Deep Learning Architectures for Person Re-identification—0
Learning to Purification for Unsupervised Person Re-identification—0
Multi-Scale Learning for Low-Resolution Person Re-Identification—0
Multi-shot Person Re-identification through Set Distance with Visual Distributional Representation—0
Multi-Shot Person Re-Identification via Relational Stein Divergence—0
Multistage Adversarial Losses for Pose-Based Human Image Synthesis—0
Multi-Stage Spatio-Temporal Aggregation Transformer for Video Person Re-identification—0
Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project—0
Multi-Task Learning With Low Rank Attribute Embedding for Person Re-Identification—0
Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification—0
Mutual Information Guided Optimal Transport for Unsupervised Visible-Infrared Person Re-identification—0
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification—0
Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification—0
Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification—0
Neural Feature Search for RGB-Infrared Person Re-Identification—0
Nonlinear Local Metric Learning for Person Re-identification—0
Not 3D Re-ID: a Simple Single Stream 2D Convolution for Robust Video Re-identification—0
Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification—0
Occluded Person Re-identification—0
Occluded Person Re-Identification via Relational Adaptive Feature Correction Learning—0
Occluded Person Re-Identification with Deep Learning: A Survey and Perspectives—0
Occluded Person Re-Identification With Single-Scale Global Representations—0
Occlude Them All: Occlusion-Aware Attention Network for Occluded Person Re-ID—0
Occlusion-Robust Online Multi-Object Visual Tracking using a GM-PHD Filter with CNN-Based Re-Identification—0
OH-Former: Omni-Relational High-Order Transformer for Person Re-Identification—0
Omni-directional Feature Learning for Person Re-identification—0
One for More: Selecting Generalizable Samples for Generalizable ReID Model—0
One-pass Person Re-identification by Sketch Online Discriminant Analysis—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