fast-reid/projects/Cross-domain-reid

Cross-domain Person Re-Identification

Introduction

UDAStrongBaseline is a transitional code based pyTorch framework for both unsupervised learning (USL) and unsupervised domain adaptation (UDA) in the object re-ID tasks. It provides stronger baselines on these tasks. It needs the enviorment: Python >=3.6 and PyTorch >=1.1. We will transfer all the codes to the fastreid in the future (ongoing) from UDAStrongBaseline.

Unsupervised domain adaptation (UDA) on Person re-ID

• Direct Transfer models are trained on the source-domain datasets (source_pretrain) and directly tested on the target-domain datasets.
• UDA methods (MMT, SpCL, etc.) starting from ImageNet means that they are trained end-to-end in only one stage without source-domain pre-training. MLT denotes to the implementation of our NeurIPS-2020. Please note that it is a pre-released repository for the anonymous review process, and the official repository will be released upon the paper published.

DukeMTMC-reID -> Market-1501

Method	Backbone	Pre-trained	mAP(%)	top-1(%)	top-5(%)	top-10(%)	Train time
Direct Transfer	ResNet50	DukeMTMC	32.2	64.9	78.7	83.4	~1h
UDA_TP PR'2020	ResNet50	DukeMTMC	52.3	76.0	87.8	91.9	~2h
MMT ICLR'2020	ResNet50	DukeMTMC	80.9	92.2	97.6	98.4	~6h
SpCL NIPS'2020 submission	ResNet50	DukeMTMC	78.2	90.5	96.6	97.8	~3h
strong_baseline	ResNet50	DukeMTMC	75.6	90.9	96.6	97.8	~3h
Our stronger_baseline	ResNet50	DukeMTMC	78.0	91.0	96.4	97.7	~3h
[MLT] NeurIPS'2020 submission	ResNet50	DukeMTMC	81.5	92.8	96.8	97.9	~

Market-1501 -> DukeMTMC-reID

Method	Backbone	Pre-trained	mAP(%)	top-1(%)	top-5(%)	top-10(%)	Train time
Direct Transfer	ResNet50	Market	34.1	51.3	65.3	71.7	~1h
UDA_TP PR'2020	ResNet50	Market	45.7	65.5	78.0	81.7	~2h
MMT ICLR'2020	ResNet50	Market	67.7	80.3	89.9	92.9	~6h
SpCL NIPS'2020 submission	ResNet50	Market	70.4	83.8	91.2	93.4	~3h
strong_baseline	ResNet50	Market	60.4	75.9	86.2	89.8	~3h
Our stronger_baseline	ResNet50	Market	66.7	80.0	89.2	92.2	~3h
[MLT] NeurIPS'2020 submission	ResNet50	Market	71.2	83.9	91.5	93.2	~

Market1501 -> MSMT17

Method	Source	Rank@1	mAP	mINP
DirectTransfer(R50)	Market1501	29.8%	10.3%	9.3%
Our method	DukeMTMC	56.6%	26.5%	-

DukeMTMC -> MSMT17

Method	Source	Rank@1	mAP	mINP
DirectTransfer(R50)	DukeMTMC	34.8%	12.5%	0.3%
Our method	DukeMTMC	59.5%	27.7%	-