Hoi! - A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation
This dataset provides a unique resource for researchers studying articulated object manipulation by coupling visual, force, and tactile data across human and robotic embodiments.
The paper introduces a multimodal dataset for force-grounded, cross-view articulated manipulation, containing 3048 sequences across 381 objects in 38 environments, with four embodiments including human hand and robotic grippers. The dataset enables evaluation of cross-view transfer and exploration of interaction forces.
We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during real human interaction. The dataset contains 3048 sequences across 381 articulated objects in 38 environments. Each object is operated in four embodiments - (i) human hand, (ii) human hand with a wrist-mounted camera, (iii) handheld UMI gripper, and (iv) a custom Hoi! gripper, where the tool embodiment provides end-effector forces and tactile sensing. Our dataset offers a holistic view of interaction understanding from video, enabling researchers to evaluate how well methods transfer between human and robotic viewpoints, but also investigate underexplored modalities such as interaction forces. The Project Website can be found at https://timengelbracht.github.io/Hoi-Dataset-Website/.