Corpus ID: 236170864

PoseDet: Fast Multi-Person Pose Estimation Using Pose Embedding

@article{Tian2021PoseDetFM,
  title={PoseDet: Fast Multi-Person Pose Estimation Using Pose Embedding},
  author={Chenyu Tian and Ran Yu and Xinyuan Zhao and Weihao Xia and Haoqian Wang and Yujiu Yang},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.10466}
}
Current methods of multi-person pose estimation typically treat the localization and the association of body joints separately. It is convenient but inefficient, leading to additional computation and a waste of time. This paper, however, presents a novel framework PoseDet (Estimating Pose by Detection) to localize and associate body joints simultaneously at higher inference speed. Moreover, we propose the keypoint-aware pose embedding to represent an object in terms of the locations of its… Expand

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References

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An approach that jointly solves the tasks of detection and pose estimation: it infers the number of persons in a scene, identifies occluded body parts, and disambiguates body parts between people in close proximity of each other is proposed. Expand
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