5 papers · 1 filter
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…
4D Reconstruction from Sparse Dynamic Cameras
Kazuki Ozeki, Shun Kenney, Yuto Shibata +6
Although dynamic 3D (i.e., 4D) reconstruction from a monocular dynamic camera has recently advanced, it remains fundamentally limited by depth ambiguity. In this paper, we focus on…
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…
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…
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs
Yuto Shibata, Yasunori Kudo, Yohei Sugawara
In this study, we propose a novel federated learning (FL) approach that utilizes 3D style transfer for the multi-organ segmentation task. The multi-organ dataset, obtained by integ…