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 301–350 of 1488 papers

TitleStatusHype
Learning Diverse Features with Part-Level Resolution for Person Re-IdentificationCode1
Learning Feature Recovery Transformer for Occluded Person Re-identificationCode1
An In-Depth Exploration of Person Re-Identification and Gait Recognition in Cloth-Changing ConditionsCode1
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine LearningCode1
Learning Modal-Invariant and Temporal-Memory for Video-based Visible-Infrared Person Re-IdentificationCode1
Learning Multi-Attention Context Graph for Group-Based Re-IdentificationCode1
Benchmarks for Corruption Invariant Person Re-identificationCode1
DeepChange: A Long-Term Person Re-Identification Benchmark with Clothes ChangeCode1
Fine-Grained Re-IdentificationCode1
Learning With Twin Noisy Labels for Visible-Infrared Person Re-IdentificationCode1
Deep Cosine Metric Learning for Person Re-IdentificationCode1
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationCode1
Lightweight Multi-Branch Network for Person Re-IdentificationCode1
IDM: An Intermediate Domain Module for Domain Adaptive Person Re-IDCode1
MARS: Paying more attention to visual attributes for text-based person searchCode1
DIFFER: Disentangling Identity Features via Semantic Cues for Clothes-Changing Person Re-IDCode1
Deep High-Resolution Representation Learning for Cross-Resolution Person Re-identificationCode1
Masked Attribute Description Embedding for Cloth-Changing Person Re-identificationCode1
MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-IdentificationCode1
Diverse Representation Embedding for Lifelong Person Re-IdentificationCode1
MobileNetV2: Inverted Residuals and Linear BottlenecksCode1
Deep Learning for Person Re-identification: A Survey and OutlookCode1
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
Multi-direction and Multi-scale Pyramid in Transformer for Video-based Pedestrian RetrievalCode1
Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-IdentificationCode1
Self-Supervised Pre-Training for Transformer-Based Person Re-IdentificationCode1
Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identificationCode1
Contrastive Multiple Instance Learning for Weakly Supervised Person ReID—0
Continuous Adaptation of Multi-Camera Person Identification Models through Sparse Non-redundant Representative Selection—0
A Little Bit Attention Is All You Need for Person Re-Identification—0
Context Sensing Attention Network for Video-based Person Re-identification—0
Context-Aware Unsupervised Clustering for Person Search—0
Attribute analysis with synthetic dataset for person re-identification—0
Attribute Adaptive Margin Softmax Loss using Privileged Information—0
AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification—0
Constrained Dominant sets and Its applications in computer vision—0
Constrained Deep Metric Learning for Person Re-identification—0
Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification—0
DualFocus: Integrating Plausible Descriptions in Text-based Person Re-identification—0
Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification—0
Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network—0
Confidence-guided Centroids for Unsupervised Person Re-Identification—0
Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification—0
Compact Network Training for Person ReID—0
Aligned Divergent Pathways for Omni-Domain Generalized Person Re-Identification—0
Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person Re-identification—0
Combining Two Adversarial Attacks Against Person Re-Identification Systems—0
Attention Driven Person Re-identification—0
Colors See Colors Ignore: Clothes Changing ReID with Color Disentanglement (ICCV-25 🥳)—0
DSAM: A Distance Shrinking with Angular Marginalizing Loss for High Performance Vehicle Re-identificatio—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
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