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 401425 of 1488 papers

TitleStatusHype
DiP: Learning Discriminative Implicit Parts for Person Re-IdentificationCode0
Adversarial Metric Attack and Defense for Person Re-identificationCode0
Camera Alignment and Weighted Contrastive Learning for Domain Adaptation in Video Person ReIDCode0
MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-IdentificationCode0
Adaptive Domain-Specific Normalization for Generalizable Person Re-IdentificationCode0
Differentiable Channel Selection in Self-Attention For Person Re-IdentificationCode0
Learning Transferable Pedestrian Representation from Multimodal Information SupervisionCode0
Appearance and Pose-Conditioned Human Image Generation using Deformable GANsCode0
Leveraging Virtual and Real Person for Unsupervised Person Re-identificationCode0
Devil in the Details: Towards Accurate Single and Multiple Human ParsingCode0
Learning Intra and Inter-Camera Invariance for Isolated Camera Supervised Person Re-identificationCode0
Learning Invariance from Generated Variance for Unsupervised Person Re-identificationCode0
CILP-FGDI: Exploiting Vision-Language Model for Generalizable Person Re-IdentificationCode0
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identificationCode0
A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-RankingCode0
Learning Robust Visual-Semantic Embedding for Generalizable Person Re-identificationCode0
2017 Robotic Instrument Segmentation ChallengeCode0
Learning from Synchronization: Self-Supervised Uncalibrated Multi-View Person Association in Challenging ScenesCode0
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free ApproachCode0
Learning Disentangled Representation for Robust Person Re-identificationCode0
Learning to Disentangle Scenes for Person Re-identificationCode0
DROP: Decouple Re-Identification and Human Parsing with Task-specific Features for Occluded Person Re-identificationCode0
Mask-Guided Contrastive Attention Model for Person Re-IdentificationCode0
Leaning Compact and Representative Features for Cross-Modality Person Re-IdentificationCode0
LCM: Log Conformal Maps for Robust Representation Learning to Mitigate Perspective DistortionCode0
Show:102550
← PrevPage 17 of 60Next →

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
10SOLIDER (RK)Rank-196.7Unverified
#ModelMetricClaimedVerifiedStatus
1DenseILmAP97.1Unverified
2CTL Model (ResNet50, 256x128)mAP96.1Unverified
3BPBreID (RK)mAP92.9Unverified
4Unsupervised Pre-training (ResNet101+RK)mAP92.77Unverified
5st-ReID(RE, RK,Cam)mAP92.7Unverified
6RGT&RGPR (RK)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