Person Re-Identification on DukeMTMC-reID

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mAP

Rank	Model	mAP	Rank-1	Rank-5	Rank-10	Rank-1	Rank-5	Extra Training Data	Paper	Code	Year
1	DenseIL	97.1	–	–	–	–	–		Dense Interaction Learning for Video-based Person Re-identification		2021
2	CTL Model (ResNet50, 256x128)	96.1	95.6	96.2	97.9	–	–		On the Unreasonable Effectiveness of Centroids in Image Retrieval	mikwieczorek/centroids-reid · lannguyen0910/deep-efficient-reid · lannguyen0910/deep-efficient-person-reid	2021
3	BPBreID (RK)	92.9	93.9	–	–	–	–		Body Part-Based Representation Learning for Occluded Person Re-Identification	vlsomers/bpbreid · trackinglaboratory/tracklab · vlsomers/keypoint_promptable_reidentification	2022
4	Unsupervised Pre-training (ResNet101+RK)	92.77	93.99	–	–	–	–	✓	Unsupervised Pre-training for Person Re-identification	DengpanFu/LUPerson	2020
5	st-ReID(RE, RK,Cam)	92.7	94.5	–	–	–	–		Spatial-Temporal Person Re-identification	Wanggcong/Spatial-Temporal-Re-identification · SurajDonthi/Multi-Camera-Person-Re-Identification · BonaventureR/person-reid	2018
5	RGT&RGPR (RK)	92.7	94.3	–	–	–	–	✓	Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method	finger-monkey/Data-Augmentation	2021
7	Viewpoint-Aware Loss(RK)	91.8	93.9	96.5	–	–	–	✓	Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification	zzhsysu/VA-ReID	2019
8	LDS (ResNet50 + RK)	91.0	92.91	–	–	–	–		Learning to Disentangle Scenes for Person Re-identification	deropty/LDS	2021
9	FlipReID (with re-ranking)	90.7	93.0	–	–	–	–		FlipReID: Closing the Gap between Training and Inference in Person Re-Identification	nixingyang/FlipReID	2021
9	Adaptive L2 Regularization (with re-ranking)	90.7	92.2	–	–	–	–		Adaptive L2 Regularization in Person Re-Identification	nixingyang/AdaptiveL2Regularization	2020
11	DAAF-BoT(RK)	89.6	91.7	–	–	–	–		Deep Attention Aware Feature Learning for Person Re-Identification	CYFFF/DAAF_re-id · 2023-MindSpore-1/ms-code-71	2020
12	RPTM	89.2	93.5	96.1	–	–	–		Relation Preserving Triplet Mining for Stabilising the Triplet Loss in Re-identification Systems	adhirajghosh/rptm_reid	2021
12	Auto-ReID(RK)	89.2	91.4	–	–	–	–		Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification	D-X-Y/GDAS · D-X-Y/NAS-Projects · DuanYiqun/Auto-ReID-Fast	2019
14	BoT Baseline(RK)	89.1	90.2	–	–	–	–		Bag of Tricks and A Strong Baseline for Deep Person Re-identification	PaddlePaddle/PaddleClas · layumi/Person_reID_baseline_pytorch · michuanhaohao/reid-strong-baseline · +5	2019
14	st-ReID+InSTD	89.1	–	–	–	–	–		Learning Instance-level Spatial-Temporal Patterns for Person Re-identification	RenMin1991/cleaned-DukeMTMC-reID	2021
16	Top-DB-Net + RK	88.6	90.9	–	–	–	–		Top-DB-Net: Top DropBlock for Activation Enhancement in Person Re-Identification	RQuispeC/top-dropblock	2020
17	DG-Net(RK)	88.31	90.26	–	–	–	–		Joint Discriminative and Generative Learning for Person Re-identification	layumi/Person_reID_baseline_pytorch · NVlabs/DG-Net · youwenjing/reid_mgn-dgnet · +9	2019
18	PyrNet (+ReRank)	87.7	90.3	–	–	–	–		Aggregating Deep Pyramidal Representations for Person Re-Idenfitication	iN1k1/deep-pyramidal-representations-person-re-identification	2019
19	Deep Constrained Dominant Sets	86.1	88.5	–	–	–	–		Deep Constrained Dominant Sets for Person Re-identification	leule/DCDS	2019
20	Parameter-Free Spatial Attention	85.9	89.0	–	–	–	–		Parameter-Free Spatial Attention Network for Person Re-Identification	HRanWang/Spatial-Attention · HRanWang/SA · schizop/SA	2018