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Found 3 papers, 1 papers with code
InterCap: Joint Markerless 3D Tracking of Humans and Objects in Interaction
With this method we capture the InterCap dataset, which contains 10 subjects (5 males and 5 females) interacting with 10 objects of various sizes and affordances, including contact with the hands or feet.
Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time
To learn from sufficient data, we synthesize IMU data from motion capture datasets.
Towards Accurate Markerless Human Shape and Pose Estimation over Time
Existing marker-less motion capture methods often assume known backgrounds, static cameras, and sequence specific motion priors, which narrows its application scenarios.
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