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 951–1000 of 1488 papers

TitleStatusHype
Deep Attention Aware Feature Learning for Person Re-IdentificationCode0
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
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identificationCode0
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective—0
Triplet Online Instance Matching Loss for Person Re-identification—0
A Convolutional Baseline for Person Re-Identification Using Vision and Language Descriptions—0
Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond—0
Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos—0
Intra-Camera Supervised Person Re-Identification—0
Towards Precise Intra-camera Supervised Person Re-identification—0
Constrained Dominant sets and Its applications in computer vision—0
Dual-Triplet Metric Learning for Unsupervised Domain Adaptation in Video-Based Face Recognition—0
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
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
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
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
AANet: Attribute Attention Network for Person Re-Identifications—0
In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label DistillationCode0
Progressive Learning Algorithm for Efficient Person Re-Identification—0
Occlusion-Robust Online Multi-Object Visual Tracking using a GM-PHD Filter with CNN-Based Re-Identification—0
Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-IdentificationCode0
Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-IdentificationCode0
Viewpoint-Aware Loss with Angular Regularization for Person Re-IdentificationCode0
Collaborative Attention Network for Person Re-identification—0
Spatial-Aware GAN for Unsupervised Person Re-identification—0
GBCNs: Genetic Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs—0
AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification—0
Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification—0
Relation Network for Person Re-identificationCode0
ID-aware Quality for Set-based Person Re-identificationCode0
Unified Multifaceted Feature Learning for Person Re-Identification—0
DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification—0
Visual Similarity Attention—0
Distribution Context Aware Loss for Person Re-identification—0
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss—0
A Spectral Nonlocal Block for Neural Networks—0
Progressive Sample Mining and Representation Learning for One-Shot Person Re-identification with Adversarial SamplesCode0
Weakly Supervised Tracklet Person Re-Identification by Deep Feature-wise Mutual Learning—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