623 citations
- The University of TokyoJP31 papers
- Tokyo Institute of TechnologyJP24 papers
- École PolytechniqueFR16 papers
- Future University HakodateJP10 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR10 papers
- Data61AU9 papers
- Centre National de la Recherche ScientifiqueFR8 papers
- Chuo UniversityJP6 papers
- Sony Corporation (United States)US6 papers
- Keio UniversityJP5 papers
- Kyoto UniversityJP5 papers
- Sapienza University of RomeIT5 papers
176 papers
Prosthesis-Aware 3D Human Pose Estimation: A Dataset and Benchmark for RSP Users
Yilin Wen, Kechuan Dong, Fumiya Suginaka +2
Recovering 3D human body motion from video is important for applications such as rehabilitation assessment and sports performance evaluation. For prosthesis users, this requires ca…
Coachable agents for interactive gameplay
Roberto Capobianco, Harm van Seijen, Nolan D. Bard +38
Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing to robotics to foundation m…
Physics Models for Sim-to-Real Transfer in Professional-Level Robot Table Tennis
Christian Conti, Bilan Yang, Alexander Sigrist +4
At competitive speeds and spins, a table tennis ball follows complex, counterintuitive trajectories that a robot must track and precisely counter within fractions of a second. Trai…
Profy: Interpretable Visualization of Expertise-Dependent Motor Skills Toward Supporting Piano Practice
Kazuki Kawamura, Fujiki Nakamura, Hayato Nishioka +3
The quality of piano performance depends on nuanced timing, articulation, and dynamic control, but practice feedback is often summary-based and hard to act on. We introduce Profy,…
NasoVoce: A Nose-Mounted Low-Audibility Speech Interface for Always-Available Speech Interaction
Jun Rekimoto, Yu Nishimura, Bojian Yang
Silent and whispered speech offer promise for always-available voice interaction with AI, yet existing methods struggle to balance vocabulary size, wearability, silence, and noise…
Beyond Symbols: Motion Perception Cues Enhance Dual-Task Performance with Wearable Directional Guidance
Qing Zhang, Junyu Chen, Yifei Huang +4
Directional cues are crucial for environmental interaction. Conventional methods rely on symbolic visual or auditory reminders that require semantic interpretation, a process that…