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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

PoseHD: Boosting Human Detectors Using Human Pose Information

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Zhijian Liu

Shanghai Jiao Tong University


Bowen Pan

Shanghai Jiao Tong University


Yuliang Xiu

Shanghai Jiao Tong University


Cewu Lu

Shanghai Jiao Tong University


DOI:

10.1609/aaai.v32i1.12285


Abstract:

As most recently proposed methods for human detection have achieved a sufficiently high recall rate within a reasonable number of proposals, in this paper, we mainly focus on how to improve the precision rate of human detectors. In order to address the two main challenges in precision improvement, i.e., i) hard background instances and ii) redundant partial proposals, we propose the novel PoseHD framework, a top-down pose-based approach on the basis of an arbitrary state-of-the-art human detector. In our proposed PoseHD framework, we first make use of human pose estimation (in a batch manner) and present pose heatmap classification (by a convolutional neural network) to eliminate hard negatives by extracting the more detailed structural information; then, we utilize pose-based proposal clustering and reranking modules, filtering redundant partial proposals by comprehensively considering both holistic and part information. The experimental results on multiple pedestrian benchmark datasets validate that our proposed PoseHD framework can generally improve the overall performance of recent state-of-the-art human detectors (by 2-4% in both mAP and MR metrics). Moreover, our PoseHD framework can be easily extended to object detection with large-scale object part annotations. Finally, in this paper, we present extensive ablative analysis to compare our approach with these traditional bottom-up pose-based models and highlight the importance of our framework design decisions.

Topics: AAAI

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HOW TO CITE:

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu PoseHD: Boosting Human Detectors Using Human Pose Information Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu PoseHD: Boosting Human Detectors Using Human Pose Information AAAI 2018, .

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu (2018). PoseHD: Boosting Human Detectors Using Human Pose Information. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. PoseHD: Boosting Human Detectors Using Human Pose Information. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. 2018. PoseHD: Boosting Human Detectors Using Human Pose Information. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. (2018) "PoseHD: Boosting Human Detectors Using Human Pose Information", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu, "PoseHD: Boosting Human Detectors Using Human Pose Information", AAAI, p., 2018.

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. "PoseHD: Boosting Human Detectors Using Human Pose Information". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. "PoseHD: Boosting Human Detectors Using Human Pose Information". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Zhijian Liu||Bowen Pan||Yuliang Xiu||Cewu Lu. PoseHD: Boosting Human Detectors Using Human Pose Information. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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