FastReID: A Pytorch Toolbox for General Instance Re-identification

被引:54
作者
He, Lingxiao [1 ]
Liao, Xingyu [2 ]
Liu, Wu [1 ]
Liu, Xinchen [1 ]
Cheng, Peng [1 ]
Mei, Tao [1 ]
机构
[1] JD Explore Acad, Beijing, Peoples R China
[2] Univ Sci & Technol China, Hefei, Peoples R China
来源
PROCEEDINGS OF THE 31ST ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2023 | 2023年
关键词
FastReID; Person Re-identification; Vehicle Re-identification; PyTorch Toolbox;
D O I
10.1145/3581783.3613460
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
General Instance Re-identification is a very important task in computer vision, which can be widely used in many practical applications, such as person/vehicle re-identification, face recognition, wildlife protection, commodity tracing, snapshots, and so on. To meet the increasing application demand for general instance re-identification, we present FastReID as a widely used software system. In FastReID, the 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. Moreover, we 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, it can reproduce our project results very easily. The source codes and models have been released with many users and have received over 3000 stars and 800 forks at https://github.com/JDAICV/fast-reid.
引用
收藏
页码:9664 / 9667
页数:4
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