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

Showing 526550 of 1488 papers

TitleStatusHype
Leaning Compact and Representative Features for Cross-Modality Person Re-IdentificationCode0
Learning Disentangled Representation for Robust Person Re-identificationCode0
Joint Progressive Knowledge Distillation and Unsupervised Domain AdaptationCode0
Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-IdentificationCode0
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-IdentificationCode0
Joint Detection and Identification Feature Learning for Person SearchCode0
Invisible Backdoor Attack with Dynamic Triggers against Person Re-identificationCode0
Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-IdentificationCode0
In Defense of the Triplet Loss for Person Re-IdentificationCode0
Interaction-and-Aggregation Network for Person Re-identificationCode0
In Defense of the Classification Loss for Person Re-IdentificationCode0
An Empirical Study of Person Re-Identification with AttributesCode0
In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label DistillationCode0
Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network ModelsCode0
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of AttentionCode0
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identificationCode0
Illumination Distillation Framework for Nighttime Person Re-Identification and A New BenchmarkCode0
GAF-Net: Video-Based Person Re-Identification via Appearance and Gait RecognitionsCode0
Improved Instance Discrimination and Feature Compactness for End-to-End Person SearchCode0
Incremental Learning in Person Re-IdentificationCode0
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identificationCode0
IAUnet: Global Context-Aware Feature Learning for Person Re-IdentificationCode0
ID-aware Quality for Set-based Person Re-identificationCode0
Fusion for Visual-Infrared Person ReID in Real-World Surveillance Using Corrupted Multimodal DataCode0
HydraPlus-Net: Attentive Deep Features for Pedestrian AnalysisCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1st-ReID(RE, RK)Rank-198Unverified
2SSKD(GH)Rank-197.36Unverified
3CLIP-ReID+Pose2ID (no RK)Rank-197.3Unverified
4SOLIDER +UFFM+AMCRank-197Unverified
5Unsupervised Pre-training (ResNet101+MGN)Rank-197Unverified
6RGT&RGPR (RK)Rank-196.9Unverified
7SOLIDERRank-196.9Unverified
8LightMBN (RR)Rank-196.8Unverified
9Viewpoint-Aware Loss(RK)Rank-196.79Unverified
10TransReID-SSL (ViT-B w/o RK)Rank-196.7Unverified
#ModelMetricClaimedVerifiedStatus
1DenseILmAP97.1Unverified
2CTL Model (ResNet50, 256x128)mAP96.1Unverified
3BPBreID (RK)mAP92.9Unverified
4Unsupervised Pre-training (ResNet101+RK)mAP92.77Unverified
5RGT&RGPR (RK)mAP92.7Unverified
6st-ReID(RE, RK,Cam)mAP92.7Unverified
7Viewpoint-Aware Loss(RK)mAP91.8Unverified
8LDS (ResNet50 + RK)mAP91Unverified
9Adaptive L2 Regularization (with re-ranking)mAP90.7Unverified
10FlipReID (with re-ranking)mAP90.7Unverified