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FastReID: A Pytorch Toolbox for General Instance Re-identification

About

General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identification, face recognition, wildlife protection, commodity tracing, and snapshop, etc.. To meet the increasing application demand for general instance re-identification, we present FastReID as a widely used software system in JD AI Research. In FastReID, highly modular and extensible design makes it easy for the researcher to achieve new research ideas. Friendly manageable system configuration and engineering deployment functions allow practitioners to quickly deploy models into productions. We have implemented some state-of-the-art projects, including person re-id, partial re-id, cross-domain re-id and vehicle re-id, and plan to release these pre-trained models on multiple benchmark datasets. FastReID is by far the most general and high-performance toolbox that supports single and multiple GPU servers, you can reproduce our project results very easily and are very welcome to use it, the code and models are available at https://github.com/JDAI-CV/fast-reid.

Lingxiao He, Xingyu Liao, Wu Liu, Xinchen Liu, Peng Cheng, Tao Mei• 2020

Related benchmarks

TaskDatasetResultRank
Person Re-IdentificationMarket1501 (test)
Rank-1 Accuracy95.1
1264
Person Re-IdentificationDuke MTMC-reID (test)
Rank-189.6
1018
Person Re-IdentificationMarket 1501
mAP95.3
999
Person Re-IdentificationDukeMTMC-reID
Rank-1 Acc89.6
648
Person Re-IdentificationMSMT17 (test)
Rank-1 Acc85.1
499
Person Re-IdentificationMSMT17
mAP0.769
404
Person Re-IdentificationMarket-1501 (test)
Rank-195.4
384
Person Re-IdentificationMarket-1501 to DukeMTMC-reID (test)
Rank-182.7
172
Person Re-IdentificationDukeMTMC
R1 Accuracy94.4
120
Person Re-IdentificationDukeMTMC-reID to Market-1501 (test)
Rank-1 Acc92.7
119
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Other info

Code

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