FastV2C-HandNet: Fast Voxel to Coordinate Hand Pose Estimation with 3D Convolutional Neural Networks

@article{Lekhwani2019FastV2CHandNetFV,
  title={FastV2C-HandNet: Fast Voxel to Coordinate Hand Pose Estimation with 3D Convolutional Neural Networks},
  author={Rohan Lekhwani},
  journal={ArXiv},
  year={2019},
  volume={abs/1907.06327}
}
Hand pose estimation from monocular depth images has been an important and challenging problem in the Computer Vision community. In this paper, we present a novel approach to estimate 3D hand joint locations from 2D depth images. Unlike most of the previous methods, our model using a voxel to coordinate(V2C) approach captures the 3D spatial information from a depth image using 3D CNNs thereby giving it a greater understanding of the input. We voxelize the input depth map to capture the 3D… 
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Human Pose Estimation Using Per-Point Body Region Assignment

This paper introduces a novel two-stage deep learning approach named Segmentation-Guided Pose Estimation (SGPE), based on two neural networks working in a sequential fashion, while both models effectively process unorganized point clouds on the input.

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