Perceiving Systems
PS:License 1.0
2018-10-16
Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time

This is the code for our SIGGRAPH Asia 2018 project <Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time>. The BiRNN model training and testing parts along with real-time demo are released to facilitate reproductivity and future research. The large-scale synthetic dataset and real DIP-IMU we introduced in the paper are compatible with this code, and can be accessed via the project page.
Release Date: | 16 October 2018 |
licence_type: | PS:License 1.0 |
Authors: | Yinghao Huang and Manuel Kaufmann and Emre Aksan and Michael J. Black and Otmar Hilliges and Gerard Pons-Moll |
Link (URL): | http://dip.is.tuebingen.mpg.de/ |
Repository: | https://github.com/eth-ait/dip18 |