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Found 5 papers, 4 papers with code
Hand-Object Interaction Controller (HOIC): Deep Reinforcement Learning for Reconstructing Interactions with Physics
Hand manipulating objects is an important interaction motion in our daily activities.
Fusing Monocular Images and Sparse IMU Signals for Real-time Human Motion Capture
We believe that the combination is complementary and able to solve the inherent difficulties of using one modality input, including occlusions, extreme lighting/texture, and out-of-view for visual mocap and global drifts for inertial mocap.
Ranked #1 on
3D Human Pose Estimation
on AIST++
EgoLocate: Real-time Motion Capture, Localization, and Mapping with Sparse Body-mounted Sensors
We integrate the two techniques together in EgoLocate, a system that simultaneously performs human motion capture (mocap), localization, and mapping in real time from sparse body-mounted sensors, including 6 inertial measurement units (IMUs) and a monocular phone camera.
Physical Interaction: Reconstructing Hand-object Interactions with Physics
Single view-based reconstruction of hand-object interaction is challenging due to the severe observation missing caused by occlusions.
TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors
For global translation estimation, we propose a supporting-foot-based method and an RNN-based method to robustly solve for the global translations with a confidence-based fusion technique.
