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 901–950 of 1488 papers

TitleStatusHype
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification—0
Video-based Person Re-Identification using Gated Convolutional Recurrent Neural Networks—0
Multi-task Learning with Coarse Priors for Robust Part-aware Person Re-identificationCode1
Triplet Permutation Method for Deep Learning of Single-Shot Person Re-IdentificationCode0
High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-IdentificationCode1
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric LearningCode2
Learning Shape Representations for Clothing Variations in Person Re-Identification—0
Structured Domain Adaptation with Online Relation Regularization for Unsupervised Person Re-IDCode1
Improved Baselines with Momentum Contrastive LearningCode1
Domain Adversarial Training for Infrared-colour Person Re-Identification—0
When Person Re-identification Meets Changing Clothes—0
Unity Style Transfer for Person Re-Identification—0
Deep Attention Aware Feature Learning for Person Re-IdentificationCode0
FMT:Fusing Multi-task Convolutional Neural Network for Person Search—0
Cross-Spectrum Dual-Subspace Pairing for RGB-infrared Cross-Modality Person Re-Identification—0
Cross-modality Person re-identification with Shared-Specific Feature Transfer—0
Weakly supervised discriminative feature learning with state information for person identificationCode1
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective—0
Circle Loss: A Unified Perspective of Pair Similarity OptimizationCode1
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identificationCode0
Triplet Online Instance Matching Loss for Person Re-identification—0
A Convolutional Baseline for Person Re-Identification Using Vision and Language Descriptions—0
Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos—0
Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond—0
A Simple Framework for Contrastive Learning of Visual RepresentationsCode2
Constrained Dominant sets and Its applications in computer vision—0
Intra-Camera Supervised Person Re-Identification—0
Towards Precise Intra-camera Supervised Person Re-identification—0
Dual-Triplet Metric Learning for Unsupervised Domain Adaptation in Video-Based Face Recognition—0
Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-IdentificationCode1
Diversity-Achieving Slow-DropBlock Network for Person Re-Identification—0
Adaptive Deep Metric Embeddings for Person Re-Identification under Occlusions—0
Deep Fusion Feature Representation Learning with Hard Mining Center-Triplet Loss for Person Re-identificationCode0
Person Re-identification by Contour Sketch under Moderate Clothing ChangeCode1
Illumination adaptive person reid based on teacher-student model and adversarial training—0
Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification FrameworksCode0
An Empirical Study of Person Re-Identification with AttributesCode0
Progressive Local Filter Pruning for Image Retrieval Acceleration—0
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationCode1
Learning Diverse Features with Part-Level Resolution for Person Re-IdentificationCode1
VMRFANet:View-Specific Multi-Receptive Field Attention Network for Person Re-identification—0
Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis—0
Deep Learning for Person Re-identification: A Survey and OutlookCode1
Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory—0
Learning landmark guided embeddings for animal re-identification—0
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification—0
Ranking and Classification driven Feature Learning for Person Re_identificationCode0
Ordered or Orderless: A Revisit for Video based Person Re-Identification—0
Unsupervised Few-shot Learning via Self-supervised Training—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