Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision

@article{Mehta2016Monocular3H,
  title={Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision},
  author={Dushyant Mehta and Helge Rhodin and Dan Casas and Pascal Fua and Oleksandr Sotnychenko and Weipeng Xu and Christian Theobalt},
  journal={2017 International Conference on 3D Vision (3DV)},
  year={2016},
  pages={506-516}
}
We propose a CNN-based approach for 3D human body pose estimation from single RGB images that addresses the issue of limited generalizability of models trained solely on the starkly limited publicly available 3D pose data. Using only the existing 3D pose data and 2D pose data, we show state-of-the-art performance on established benchmarks through transfer of learned features, while also generalizing to in-the-wild scenes. We further introduce a new training set for human body pose estimation… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 79 REFERENCES

Synthesizing Training Images for Boosting Human 3D Pose Estimation

  • 2016 Fourth International Conference on 3D Vision (3DV)
  • 2016
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

2D Human Pose Estimation: New Benchmark and State of the Art Analysis

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

DeepPose: Human Pose Estimation via Deep Neural Networks

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

ImageNet Large Scale Visual Recognition Challenge

  • International Journal of Computer Vision
  • 2014
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Deep Kinematic Pose Regression

VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL