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

Showing 501525 of 1488 papers

TitleStatusHype
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 Learning0
Multi-Level Attention for Unsupervised Person Re-Identification0
Multi-Domain Joint Training for Person Re-Identification0
Short Range Correlation Transformer for Occluded Person Re-Identification0
Temporal Complementarity-Guided Reinforcement Learning for Image-to-Video Person Re-Identification0
Salient-to-Broad Transition for Video Person Re-IdentificationCode1
Augmented Geometric Distillation for Data-Free Incremental Person ReID0
FAM: Visual Explanations for the Feature Representations From Deep Convolutional Networks0
Id-Free Person Similarity Learning0
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification0
Meta Distribution Alignment for Generalizable Person Re-IdentificationCode0
Learning With Twin Noisy Labels for Visible-Infrared Person Re-IdentificationCode1
FMCNet: Feature-Level Modality Compensation for Visible-Infrared Person Re-Identification0
PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose TrackingCode1
AutoLoss-GMS: Searching Generalized Margin-Based Softmax Loss Function for Person Re-Identification0
Learning Memory-Augmented Unidirectional Metrics for Cross-Modality Person Re-Identification0
Quality-aware Part Models for Occluded Person Re-identification0
TAGPerson: A Target-Aware Generation Pipeline for Person Re-identificationCode1
Delving into Probabilistic Uncertainty for Unsupervised Domain Adaptive Person Re-IdentificationCode1
Unsupervised Clustering Active Learning for Person Re-identification0
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID0
Camera-aware Style Separation and Contrastive Learning for Unsupervised Person Re-identification0
Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identificationCode1
Feature Erasing and Diffusion Network for Occluded Person Re-IdentificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1st-ReID(RE, RK)Rank-198Unverified
2SSKD(GH)Rank-197.36Unverified
3CLIP-ReID+Pose2ID (no RK)Rank-197.3Unverified
4SOLIDER +UFFM+AMCRank-197Unverified
5Unsupervised Pre-training (ResNet101+MGN)Rank-197Unverified
6RGT&RGPR (RK)Rank-196.9Unverified
7SOLIDERRank-196.9Unverified
8LightMBN (RR)Rank-196.8Unverified
9Viewpoint-Aware Loss(RK)Rank-196.79Unverified
10TransReID-SSL (ViT-B w/o RK)Rank-196.7Unverified
#ModelMetricClaimedVerifiedStatus
1DenseILmAP97.1Unverified
2CTL Model (ResNet50, 256x128)mAP96.1Unverified
3BPBreID (RK)mAP92.9Unverified
4Unsupervised Pre-training (ResNet101+RK)mAP92.77Unverified
5RGT&RGPR (RK)mAP92.7Unverified
6st-ReID(RE, RK,Cam)mAP92.7Unverified
7Viewpoint-Aware Loss(RK)mAP91.8Unverified
8LDS (ResNet50 + RK)mAP91Unverified
9Adaptive L2 Regularization (with re-ranking)mAP90.7Unverified
10FlipReID (with re-ranking)mAP90.7Unverified