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HOI-M3:Capture Multiple Humans and Objects Interaction within Contextual Environment
Humans naturally interact with both others and the surrounding multiple objects, engaging in various social activities.
LiveHPS: LiDAR-based Scene-level Human Pose and Shape Estimation in Free Environment
For human-centric large-scale scenes, fine-grained modeling for 3D human global pose and shape is significant for scene understanding and can benefit many real-world applications.
I'M HOI: Inertia-aware Monocular Capture of 3D Human-Object Interactions
In this paper, we present I'm-HOI, a monocular scheme to faithfully capture the 3D motions of both the human and object in a novel setting: using a minimal amount of RGB camera and object-mounted Inertial Measurement Unit (IMU).
LiDAR-aid Inertial Poser: Large-scale Human Motion Capture by Sparse Inertial and LiDAR Sensors
We propose a multi-sensor fusion method for capturing challenging 3D human motions with accurate consecutive local poses and global trajectories in large-scale scenarios, only using single LiDAR and 4 IMUs, which are set up conveniently and worn lightly.
HybridCap: Inertia-aid Monocular Capture of Challenging Human Motions
Monocular 3D motion capture (mocap) is beneficial to many applications.
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