Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving

@article{Zheng2021Multimodal3H,
  title={Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving},
  author={Jingxiao Zheng and Xin Yu Shi and Alexander N. Gorban and Junhua Mao and Yang Song and C. Qi and Ting Liu and Visesh Chari and Andre Cornman and Yin Zhou and Congcong Li and Drago Anguelov},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2021},
  pages={4477-4486}
}
  • Jingxiao ZhengX. Shi Drago Anguelov
  • Published 22 December 2021
  • Computer Science
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps, failure modes for LiDAR, relative location between the camera and LiDAR, and a high bar for estimation accuracy. Data collected for other use cases (such as virtual reality, gaming, and animation) may therefore not be usable for AV applications. This necessitates the collection and annotation of a large amount of 3D… 

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