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 701–750 of 1488 papers

TitleStatusHype
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
Robust Duality Learning for Unsupervised Visible-Infrared Person Re-Identification—0
Robust Knowledge Adaptation for Federated Unsupervised Person ReID—0
Robust Online Multi-target Visual Tracking using a HISP Filter with Discriminative Deep Appearance Learning—0
Robust Person Identification: A WiFi Vision-based Approach—0
Robust Person Re-Identification through Contextual Mutual Boosting—0
Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification—0
Running Event Visualization using Videos from Multiple Cameras—0
Salience-Guided Cascaded Suppression Network for Person Re-Identification—0
Sample-Specific SVM Learning for Person Re-Identification—0
SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification—0
Scalable Metric Learning via Weighted Approximate Rank Component Analysis—0
Scalable Person Re-Identification: A Benchmark—0
Scalable Person Re-identification on Supervised Smoothed Manifold—0
SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification—0
SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification—0
SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification—0
SEAS: ShapE-Aligned Supervision for Person Re-Identification—0
Second-order Non-local Attention Networks for Person Re-identification—0
Second-Order Non-Local Attention Networks for Person Re-Identification—0
See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-Identification—0
Self-Critical Attention Learning for Person Re-Identification—0
Self-Paced Uncertainty Estimation for One-shot Person Re-Identification—0
VILLS -- Video-Image Learning to Learn Semantics for Person Re-Identification—0
Semantically Selective Augmentation for Deep Compact Person Re-Identification—0
Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification—0
Semantics-Guided Clustering with Deep Progressive Learning for Semi-Supervised Person Re-identification—0
Semi-Supervised Coupled Dictionary Learning for 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