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 851–900 of 1488 papers

TitleStatusHype
Unsupervised Domain Adaptive Learning via Synthetic Data for Person Re-identification—0
Unsupervised Domain-Adaptive Person Re-identification Based on Attributes—0
Unsupervised Domain Adaptive Person Re-Identification via Human Learning Imitation—0
Unsupervised domain-adaptive person re-identification with multi-camera constraints—0
Unsupervised Domain Adaptive Person Re-id with Local-enhance and Prototype Dictionary Learning—0
Unsupervised Few Shot Learning via Self-supervised Training—0
Unsupervised Few-shot Learning via Self-supervised Training—0
Unsupervised Learning for Human Sensing Using Radio Signals—0
Unsupervised Long-Term Person Re-Identification with Clothes Change—0
Unsupervised multi-source domain adaptation for person re-identification via feature fusion and pseudo-label refinement—0
Unsupervised Noisy Tracklet Person Re-identification—0
Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions—0
Unsupervised Person Re-Identification by Camera-Aware Similarity Consistency Learning—0
Unsupervised Person Re-identification by Deep Learning Tracklet Association—0
Unsupervised Person Re-identification via Multi-label Classification—0
Unsupervised Person Re-identification via Simultaneous Clustering and Consistency Learning—0
Unsupervised Person Re-Identification with Multi-Label Learning Guided Self-Paced Clustering—0
Unsupervised Salience Learning for Person Re-identification—0
Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos—0
Unsupervised Video Person Re-identification via Noise and Hard frame Aware Clustering—0
Unsupervised Visible-Infrared Person ReID by Collaborative Learning with Neighbor-Guided Label Refinement—0
Unsupervised Visible-Infrared ReID via Pseudo-label Correction and Modality-level Alignment—0
Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system—0
User-Level Membership Inference Attack against Metric Embedding Learning—0
Using Auxiliary Information for Person Re-Identification -- A Tutorial Overview—0
Vehicle Re-identification Based on Dual Distance Center Loss—0
Video-Based Convolutional Attention for Person Re-Identification—0
Video-based Person Re-Identification using Gated Convolutional Recurrent Neural Networks—0
Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention—0
Video-based Person Re-identification with Accumulative Motion Context—0
Video-based Person Re-identification with Long Short-Term Representation Learning—0
Video-based Person Re-identification with Two-stream Convolutional Network and Co-attentive Snippet Embedding—0
Video Person Re-identification by Temporal Residual Learning—0
Video Person Re-identification using Attribute-enhanced Features—0
Video Person Re-Identification using Learned Clip Similarity Aggregation—0
Video Person Re-Identification With Competitive Snippet-Similarity Aggregation and Co-Attentive Snippet Embedding—0
Video Temporal Relationship Mining for Data-Efficient Person Re-identification—0
View Confusion Feature Learning for Person Re-identification—0
ViFi-ReID: A Two-Stream Vision-WiFi Multimodal Approach for Person Re-identification—0
Visible-Infrared Person Re-Identification via Patch-Mixed Cross-Modality Learning—0
Vista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs—0
Visual Person Understanding through Multi-Task and Multi-Dataset Learning—0
Visual Recognition-Driven Image Restoration for Multiple Degradation With Intrinsic Semantics Recovery—0
VMRFANet:View-Specific Multi-Receptive Field Attention Network for Person Re-identification—0
VRSTC: Occlusion-Free Video Person Re-Identification—0
Weakly Supervised Person Re-Identification—0
Weakly Supervised Tracklet Person Re-Identification by Deep Feature-wise Mutual Learning—0
Weakly Supervised Visible-Infrared Person Re-Identification via Heterogeneous Expert Collaborative Consistency Learning—0
Weighted Bilinear Coding over Salient Body Parts for Person Re-identification—0
What-and-Where to Match: Deep Spatially Multiplicative Integration Networks 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
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