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 651–700 of 1488 papers

TitleStatusHype
Fused Deep Neural Network based Transfer Learning in Occluded Face Classification and Person re-Identification—0
Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-IdentificationCode0
Online Unsupervised Domain Adaptation for Person Re-identification—0
A High-Accuracy Unsupervised Person Re-identification Method Using Auxiliary Information Mined from DatasetsCode0
Learning to Purification for Unsupervised Person Re-identification—0
Towards Fewer Labels: Support Pair Active Learning for Person Re-identification—0
Implicit Sample Extension for Unsupervised Person Re-Identification—0
Label Distribution Learning for Generalizable Multi-source Person Re-identification—0
Towards Homogeneous Modality Learning and Multi-Granularity Information Exploration for Visible-Infrared Person Re-Identification—0
The Group Loss++: A deeper look into group loss for deep metric learning—0
A Free Lunch to Person Re-identification: Learning from Automatically Generated Noisy Tracklets—0
Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection—0
Federated and Generalized Person Re-identification through Domain and Feature Hallucinating—0
User-Level Membership Inference Attack against Metric Embedding Learning—0
Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification—0
Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification—0
Cross-Modality Earth Mover's Distance for Visible Thermal Person Re-Identification—0
Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification—0
Generalizable Person Re-Identification via Self-Supervised Batch Norm Test-Time Adaption—0
Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends—0
Motion-Aware Transformer For Occluded Person Re-identification—0
Unsupervised Long-Term Person Re-Identification with Clothes Change—0
Leveraging Ensembles and Self-Supervised Learning for Fully-Unsupervised Person Re-Identification and Text Authorship AttributionCode0
Hybrid Contrastive Learning with Cluster Ensemble for Unsupervised Person Re-identification—0
Feature Diversity Learning with Sample Dropout for Unsupervised Domain Adaptive Person Re-identification—0
A Novel Mix-normalization Method for Generalizable Multi-source Person Re-identification—0
RealGait: Gait Recognition for Person Re-Identification—0
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identificationCode0
Unsupervised Domain Adaptive Person Re-id with Local-enhance and Prototype Dictionary Learning—0
Multi-Level Attention for Unsupervised Person Re-Identification—0
Multi-Domain Joint Training for Person Re-Identification—0
Short Range Correlation Transformer for Occluded Person Re-Identification—0
FAM: Visual Explanations for the Feature Representations From Deep Convolutional Networks—0
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification—0
Meta Distribution Alignment for Generalizable Person Re-IdentificationCode0
Learning Memory-Augmented Unidirectional Metrics for Cross-Modality Person Re-Identification—0
Temporal Complementarity-Guided Reinforcement Learning for Image-to-Video Person Re-Identification—0
Id-Free Person Similarity Learning—0
AutoLoss-GMS: Searching Generalized Margin-Based Softmax Loss Function for Person Re-Identification—0
Augmented Geometric Distillation for Data-Free Incremental Person ReID—0
Quality-aware Part Models for Occluded Person Re-identification—0
FMCNet: Feature-Level Modality Compensation for Visible-Infrared Person Re-Identification—0
Unsupervised Clustering Active Learning for Person Re-identification—0
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID—0
Camera-aware Style Separation and Contrastive Learning for Unsupervised Person Re-identification—0
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation—0
Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification—0
Dual Cluster Contrastive learning for Object Re-IdentificationCode0
HBReID: Harder Batch for Re-identification—0
Mind Your Clever Neighbours: Unsupervised Person Re-identification via Adaptive Clustering Relationship Modeling—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
5RGT&RGPR (RK)mAP92.7—Unverified
6st-ReID(RE, RK,Cam)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