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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.