End-to-end feature pyramid network for real-time multi-person pose estimation

Dingli Luo, Songlin Du, Takeshi Ikenaga

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In computer vision, pose estimation system is widely used to construct human body transformation. However, it is hard to achieve these targets together: Stable real-time speed, variance human number and high accuracy. This paper proposes an end-to-end pose estimation network. It contains a neural network friendly representation of human pose. Then it proposes a correspond real-time end-to-end pose estimation network based on feature pyramid network structure with attention-based detection modules. This network can detect multiple humans in more than 60 fps with 384 x 384 resolution on GTX 1070 with affordable accuracy. This work shows the potential of this network structure can perform both faster and better compared with state-of-the-art results.

本文言語English
ホスト出版物のタイトルProceedings of the 16th International Conference on Machine Vision Applications, MVA 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9784901122184
DOI
出版ステータスPublished - 2019 5
外部発表はい
イベント16th International Conference on Machine Vision Applications, MVA 2019 - Tokyo, Japan
継続期間: 2019 5 272019 5 31

出版物シリーズ

名前Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019

Conference

Conference16th International Conference on Machine Vision Applications, MVA 2019
国/地域Japan
CityTokyo
Period19/5/2719/5/31

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 信号処理
  • コンピュータ ビジョンおよびパターン認識

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