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We present MocapNET2, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance (70 fps in CPU-only execution). (by FORTH-ModelBasedTracker)


Basic MocapNET repo stats
about 1 month ago

FORTH-ModelBasedTracker/MocapNET is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.

MocapNET Alternatives

Similar projects and alternatives to MocapNET based on common topics and language
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  • GitHub repo tensorflow_Realtime_Multi-Person_Pose_Estimation

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NOTE: The number of mentions on this list indicates mentions on common posts. Hence, a higher number means a better MocapNET alternative or higher similarity.


Posts where MocapNET has been mentioned. We have used some of these posts to build our list of alternatives and similar projects.
  • Simple method to pose a character using a reference image and AI pose estimation? | 2021-03-02