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Relational Learning for Joint Head and Human Detection

(AAAI2020)

Paper in arXiv

Abstract

In this work, we present a novel joint head and human detection network, namely JointDet, which effectively detects head and human body simultaneously, aiming at handling issues that head detection is often trapped in more false positives and performance of human detector frequently drops dramatically in crowd scenes.

Methods

method

Getting Started

Model Zoo

Method MR(Person) MR(Head) Config model Download
JointDet w/ RDM 45.7 48.3 config Baidu Cloud (提取码: nm8r)
Google Drive
JointDet w/o RDM 46.8 48.6 config Baidu Cloud (提取码: n6zg)
Google Drive

Citing JointDet

If this work is helpful for your research, please consider citing:

@inproceedings{chi2020relational,
  title={Relational learning for joint head and human detection},
  author={Chi, Cheng and Zhang, Shifeng and Xing, Junliang and Lei, Zhen and Li, Stan Z and Zou, Xudong},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={07},
  pages={10647--10654},
  year={2020}
}

Acknowledgement

Many thanks to following open source project:

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