Unsupervised-Person-ReID-Paper

Current Unsupervised Person ReID Paper&Code

title	abbreviation	year	d->m(M)	m->d(D)	code
Person Transfer GAN to Bridge Domain Gap for Person Re-Identification	PTGAN	CVPR2018	-	-	https://github.com/pkuvmc/PTGAN
Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification	TJ-AIDL	CVPR2018	23.0/44.3	26.5/58.2	-
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification	SPGAN	CVPR2018	26.9/58.1	26.4/46.9	https://github.com/Simon4Yan/Learning-via-Translation
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification	ARN	CVPR2018W	39.4/70.3	33.4/60.2	https://github.com/yujheli/ARN
Generalizing A Person Retrieval Model Hetero- and Homogeneously	HHL	ECCV2018	31.4/62.2	27.2/46.9	https://github.com/zhunzhong07/HHL
Unsupervised Person Re-identification by Deep Learning Tracklet Association	TAUDL	ECCV2018	41.2/63.7	43.5/61.7	-
Unsupervised Tracklet Person Re-Identification	UTAL	TPAMI2019	46.2/69.2	44.6/62.3	-
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification	ECN	CVPR2019	43.0/75.1	40.4/63.3	https://github.com/zhunzhong07/ECN
Unsupervised Person Re-identification by Soft Multilabel Learning	MAR	CVPR2019	40.0/67.7*	48.0/67.1*	https://github.com/KovenYu/MAR
Unsupervised Person Re-Identification with Iterative Self-Supervised Domain Adaptation	ISSDA-ReID	CVPR2019W	63.1/81.3	54.1/72.8	-
Patch-based discriminative feature learning for unsupervised person re-identification	PAUL	CVPR2019	40.1/68.5*	53.2/72.0*	https://github.com/QizeYang/PAUL
Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding	DECAMEL	TPAMI2019	32.44/60.24	-	https://github.com/KovenYu/DECAMEL
Learning to Adapt Invariance in Memory for Person Re-identification	ECN+GPP	TPAMI2019	63.8/84.1	54.4/74.0	-
Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification	ACAN	TIP?	50.6/73.3	46.6/65.1	-
Unsupervised Person Re-identification: Clustering and Fine-tuning	PUL	TOMCCAP17	(D,C->M) 24.8/50.9	(M,C->D) 21.5/36.5	https://github.com/hehefan/Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning
A Bottom-up Clustering Approach to Unsupervised Person Re-identification	BUC	AAAI2019	(M) 38.3/66.2 29.6/61.9	(D) 27.5/47.4 22.1/40.4	https://github.com/vana77/Bottom-up-Clustering-Person-Re-identification
Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification	DBC	Arxiv19(TMM?)	(M) 41.3/69.2	(D) 30.0/51.5	https://github.com/gddingcs/Dispersion-based-Clustering
Adaptive Exploration for Unsupervised Person Re-Identification	AE	Arxiv19(TMM?)	54.0/77.5	39.6/63.2	https://github.com/dyh127/Adaptive-Exploration-for-Unsupervised-Person-Re-Identification
Hierarchical Clustering-guided re-ID with Triplet loss	HRC	Arxiv19	(M) 55.3/79.5	(D) 46.8/66.0	-
Consistent Cross-view Matching for Unsupervised Person Re-identification	CCM	Arxiv19	(M)43.1/71.7	-	-
Unsupervised Person Re-identification via Multi-label Classification	MMCL	CVPR20	45.5/80.3	40.2/65.2	https://github.com/kennethwdk/MLCReID
Unsupervised Person Re-identification via Softened Similarity Learning	SSL	CVPR20	37.8/71.7	28.6/52.5	-
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* Means trained with MSMT17 dataset, (M) means trained with Market Only, (D) means trained with Duke Only