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20242026
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cs.CV2026

Sound-based Multi-Person 3D Pose Estimation

Yusuke Oumi, Yuto Shibata, Go Irie +3

Can we recover the 3D poses of multiple people using only sound? This paper presents the first attempt to estimate multi-person 3D poses solely from acoustic signals. Estimating th…

cs.CV2026

Mesh-Aware Epipolar Matching for Multi-View Multi-Person 3D Pose Estimation in Basketball

Li Yin, Qin Haobin, Tomohiro Suzuki +3

Multi-view multi-person 3D pose estimation in team sports scenarios remains challenging due to player occlusions, appearance similarity caused by team uniforms, and the scarcity of…

cs.CV2026

Learning to Assist: Physics-Grounded Human-Human Control via Multi-Agent Reinforcement Learning

Yuto Shibata, Kashu Yamazaki, Lalit Jayanti +3

Humanoid robotics has strong potential to transform daily service and caregiving applications. Although recent advances in general motion tracking within physics engines (GMT) have…

cs.CV2026

Image-based Joint-level Detection for Inflammation in Rheumatoid Arthritis from Small and Imbalanced Data

Shun Kato, Yasushi Kondo, Shuntaro Saito +2

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic joint inflammation. Early diagnosis and tight follow-up are essential to the management of RA, as ongoi…

cs.CV2025

BGM2Pose: Active 3D Human Pose Estimation with Non-Stationary Sounds

Yuto Shibata, Yusuke Oumi, Go Irie +3

We propose BGM2Pose, a non-invasive 3D human pose estimation method using arbitrary music (e.g., background music) as active sensing signals. Unlike existing approaches that signif…