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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–900 of 1488 papers

TitleStatusHype
Prompt-driven Transferable Adversarial Attack on Person Re-Identification with Attribute-aware Textual Inversion—0
ProtoHPE: Prototype-guided High-frequency Patch Enhancement for Visible-Infrared Person Re-identification—0
Prototype-guided Cross-modal Completion and Alignment for Incomplete Text-based Person Re-identification—0
Pseudo-label Refinement for Improving Self-Supervised Learning Systems—0
Pseudo-Pair based Self-Similarity Learning for Unsupervised Person Re-identification—0
Pseudo-positive regularization for deep person re-identification—0
PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift—0
Pyramid Person Matching Network for Person Re-identification—0
Quality-aware Part Models for Occluded Person Re-identification—0
Query Adaptive Late Fusion for Image Retrieval—0
Query-Adaptive Late Fusion for Image Search and Person Re-Identification—0
Random Occlusion-recovery for Person Re-identification—0
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification—0
Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification—0
Rapid Person Re-Identification via Sub-space Consistency Regularization—0
Angular Triplet Loss-based Camera Network for ReID—0
RealGait: Gait Recognition for Person Re-Identification—0
Real-Time Online Unsupervised Domain Adaptation for Real-World Person Re-identification—0
Real-world Person Re-Identification via Degradation Invariance Learning—0
Recent Advances of Local Mechanisms in Computer Vision: A Survey and Outlook of Recent Work—0
Receptive Multi-granularity Representation for Person Re-Identification—0
Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification—0
Rectifying the Data Bias in Knowledge Distillation—0
Recurrent Convolutional Network for Video-Based Person Re-Identification—0
Recurrent Neural Networks for Person Re-identification Revisited—0
Reference-Aided Part-Aligned Feature Disentangling for Video Person Re-Identification—0
Region-based Quality Estimation Network for Large-scale Person Re-identification—0
Region Generation and Assessment Network for Occluded Person Re-Identification—0
Re-ID done right: towards good practices for person re-identification—0
Re-ID Driven Localization Refinement for Person Search—0
Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints—0
Re-Identification Supervised Texture Generation—0
Re-Identification with Consistent Attentive Siamese Networks—0
Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification—0
Relevance Subject Machine: A Novel Person Re-identification Framework—0
ReMix: Training Generalized Person Re-identification on a Mixture of Data—0
Re-ranking Person Re-identification with k-reciprocal Encoding—0
Re-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification—0
Resolution based Feature Distillation for Cross Resolution Person Re-Identification—0
Resolution-invariant Person ReID Based on Feature Transformation and Self-weighted Attention—0
Beyond Triplet Loss: Meta Prototypical N-tuple Loss for Person Re-identification—0
Rethinking Clothes Changing Person ReID: Conflicts, Synthesis, and Optimization—0
Rethinking Person Re-identification from a Projection-on-Prototypes Perspective—0
Review of Person Re-identification Techniques—0
Revisiting the Role of Texture in 3D Person Re-identification—0
RGB-Infrared Cross-Modality Person Re-Identification—0
RGB-IR Cross-modality Person ReID based on Teacher-Student GAN Model—0
Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild—0
Robust and Efficient Graph Correspondence Transfer for Person Re-identification—0
Robust Depth-based Person Re-identification—0
Show:102550
← PrevPage 18 of 30Next →
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
10TransReID-SSL (ViT-B w/o 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