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 701–725 of 1488 papers

TitleStatusHype
Joint Learning of Single-Image and Cross-Image Representations for Person Re-Identification—0
Deep Self-Paced Learning for Person Re-Identification—0
Deep Active Learning for Video-based Person Re-identification—0
Learning landmark guided embeddings for animal re-identification—0
Joint Person Re-identification and Camera Network Topology Inference in Multiple Cameras—0
Handling Label Uncertainty for Camera Incremental Person Re-Identification—0
Learning Person Re-identification Models from Videos with Weak Supervision—0
Joint Probabilistic Matching Using m-Best Solutions—0
Hierarchical Gaussian Descriptors with Application to Person Re-Identification—0
Kernel Cross-View Collaborative Representation based Classification for Person Re-Identification—0
Hierarchical Gaussian Descriptor for Person Re-Identification—0
Decentralised Person Re-Identification with Selective Knowledge Aggregation—0
Hierarchical Cross Network for Person Re-identification—0
Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification—0
Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification—0
Knowledge Assembly: Semi-Supervised Multi-Task Learning from Multiple Datasets with Disjoint Labels—0
Dense Interaction Learning for Video-based Person Re-identification—0
Knowledge Distillation Methods for Efficient Unsupervised Adaptation Across Multiple Domains—0
Batch Coherence-Driven Network for Part-aware Person Re-Identification—0
Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification—0
Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification—0
Hierarchical and Efficient Learning for Person Re-Identification—0
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning—0
LATex: Leveraging Attribute-based Text Knowledge for Aerial-Ground Person Re-Identification—0
Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification—0
Show:102550
← PrevPage 29 of 60Next →
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