FastReID: A Pytorch Toolbox for General Instance Re-identification (2020-06-04T00:00:00.000000Z)

TL;DR

This work presents FastReID as a widely used software system that supports single and multiple GPU servers, it can reproduce the project results very easily, and has implemented some state-of-the-art projects, including person re-id, partial re-ids, cross-domain re-ID, and vehicle re-identification.

Abstract

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 at https://github.com/JDAI-CV/fast-reid.

Authors

Xinchen Liu

5 papers

Wu Liu

5 papers

Tao Mei

14 papers

TL;DR

Abstract

Authors

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