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 1401–1450 of 1488 papers

TitleStatusHype
Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images—0
Local Fisher Discriminant Analysis for Pedestrian Re-identification—0
Locally Aligned Feature Transforms across Views—0
Long-Term Cloth-Changing Person Re-identification—0
Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification—0
LVreID: Person Re-Identification with Long Sequence Videos—0
M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification—0
Making Person Search Enjoy the Merits of Person Re-identification—0
Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-identification—0
Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification—0
MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification—0
Maximum Margin Metric Learning Over Discriminative Nullspace for Person Re-identification—0
Measuring the Temporal Behavior of Real-World Person Re-Identification—0
Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory—0
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory—0
Meta Clustering Learning for Large-scale Unsupervised Person Re-identification—0
Meta Generative Attack on Person Reidentification—0
Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning—0
Metric Learning in Codebook Generation of Bag-of-Words for Person Re-identification—0
MilliTRACE-IR: Contact Tracing and Temperature Screening via mm-Wave and Infrared Sensing—0
Mind the Gap: Bridging Occlusion in Gait Recognition via Residual Gap Correction—0
Mind Your Clever Neighbours: Unsupervised Person Re-identification via Adaptive Clustering Relationship Modeling—0
Mix-Modality Person Re-Identification: A New and Practical Paradigm—0
Mixture of Submodules for Domain Adaptive Person Search—0
MLLMReID: Multimodal Large Language Model-based Person Re-identification—0
MMPTRACK: Large-scale Densely Annotated Multi-camera Multiple People Tracking Benchmark—0
Möbius Transform for Mitigating Perspective Distortions in Representation Learning—0
Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification—0
Modality Unified Attack for Omni-Modality Person Re-Identification—0
Modality Unifying Network for Visible-Infrared Person Re-Identification—0
Motion-Aware Transformer For Occluded Person Re-identification—0
MRCN: A Novel Modality Restitution and Compensation Network for Visible-Infrared Person Re-identification—0
MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification—0
Multi-Camera Industrial Open-Set Person Re-Identification and Tracking—0
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID—0
Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification—0
Multi-Channel Pyramid Person Matching Network for Person Re-Identification—0
Multi-Domain Adversarial Feature Generalization for Person Re-Identification—0
Multi-Domain Biometric Recognition using Body Embeddings—0
Multi-Domain Joint Training for Person Re-Identification—0
Multi-Expert Adversarial Attack Detection in Person Re-identification Using Context Inconsistency—0
Multi-Granularity Graph Pooling for Video-based Person Re-Identification—0
Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification—0
Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification—0
Multi-Level Attention for Unsupervised Person Re-Identification—0
Multi-Level Factorisation Net for Person Re-Identification—0
Multilinear subspace learning for person re-identification based fusion of high order tensor features—0
Multi-modal Multi-platform Person Re-Identification: Benchmark and Method—0
Multiple Domain Experts Collaborative Learning: Multi-Source Domain Generalization For Person Re-Identification—0
Multiple Information Prompt Learning for Cloth-Changing 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