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 1051–1100 of 1488 papers

TitleStatusHype
SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification—0
Real-time Person Re-identification at the Edge: A Mixed Precision ApproachCode0
Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification—0
Learning Deep Representations by Mutual Information for Person Re-identification—0
Mixed High-Order Attention Network for Person Re-IdentificationCode0
Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification—0
FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks—0
Person Re-identification in Aerial ImageryCode0
GreyReID: A Two-stream Deep Framework with RGB-grey Information for Person Re-identification—0
HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning—0
HBONet: Harmonious Bottleneck on Two Orthogonal DimensionsCode0
Temporal Knowledge Propagation for Image-to-Video Person Re-identificationCode0
Robust Online Multi-target Visual Tracking using a HISP Filter with Discriminative Deep Appearance Learning—0
Progressive Transfer LearningCode0
Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-IdentificationCode0
Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition—0
ABD-Net: Attentive but Diverse Person Re-IdentificationCode0
Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification—0
Learning to Adapt Invariance in Memory for Person Re-identification—0
Self-training with progressive augmentation for unsupervised cross-domain person re-identificationCode0
Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID—0
Learning Resolution-Invariant Deep Representations for Person Re-Identification—0
Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person Re-Identification—0
Universal Person Re-Identification—0
PH-GCN: Person Re-identification with Part-based Hierarchical Graph Convolutional Network—0
Interaction-and-Aggregation Network for Person Re-identificationCode0
VRSTC: Occlusion-Free Video Person Re-Identification—0
An Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification—0
Adaptive Exploration for Unsupervised Person Re-IdentificationCode0
A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification—0
Exploiting Prunability for Person Re-Identification—0
Resolution-invariant Person Re-IdentificationCode0
Improving Description-based Person Re-identification by Multi-granularity Image-text Alignments—0
Aggregating Deep Pyramidal Representations for Person Re-IdenfiticationCode0
CDPM: Convolutional Deformable Part Models for Semantically Aligned Person Re-identification—0
Deep Visual Re-Identification with ConfidenceCode0
HPILN: A feature learning framework for cross-modality person re-identification—0
Visual Person Understanding through Multi-Task and Multi-Dataset Learning—0
PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification—0
Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identificationCode0
Distilled Person Re-Identification: Towards a More Scalable System—0
Patch-Based Discriminative Feature Learning for Unsupervised Person Re-IdentificationCode0
Learning to Reduce Dual-Level Discrepancy for Infrared-Visible Person Re-Identification—0
Generalizable Person Re-Identification by Domain-Invariant Mapping Network—0
Re-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification—0
Adaptive Transfer Network for Cross-Domain Person Re-Identification—0
Towards Rich Feature Discovery With Class Activation Maps Augmentation for Person Re-Identification—0
Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification—0
Attention: A Big Surprise for Cross-Domain Person Re-Identification—0
Semantics-Aligned Representation Learning for Person Re-identificationCode0
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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