Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
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Although significant improvement has been achieved in 3D human pose estimation, most of the previous methods only consider a single-person case. In this work, we firstly propose a fully learning-based, camera distance-aware top-down approach for 3D multi-person pose estimation from a single RGB image. The pipeline of the proposed system consists of human detection, absolute 3D human root localization, and root-relative 3D single-person pose estimation models. Our system achieves comparable results with the state-of-the-art 3D single-person pose estimation models without any groundtruth information and significantly outperforms previous 3D multi-person pose estimation methods on publicly available datasets. The code is available in [<https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE>][<https://github.com/mks0601/3DMPPE_POSENET_RELEASE>].
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