7 papers
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…
Sign-to-Speech Prosody Transfer via Sign Reconstruction-based GAN
Toranosuke Manabe, Yuto Shibata, Shinnosuke Takamichi +1
Deep learning models have improved sign language-to-text translation and made it easier for non-signers to understand signed messages. When the goal is spoken communication, a naiv…
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…
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…
Formula-Supervised Sound Event Detection: Pre-Training Without Real Data
Yuto Shibata, Keitaro Tanaka, Yoshiaki Bando +3
In this paper, we propose a novel formula-driven supervised learning (FDSL) framework for pre-training an environmental sound analysis model by leveraging acoustic signals parametr…
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…