Shangyuan Yuan — accepted AI-conference papers

2026

AFT: Appearance-Based Feature Tracking for Markerless and Training-Free Shape Reconstruction of Soft Robots

Shangyuan Yuan, Preston Fairchild, Yu Mei, Xinyu Zhou, Xiaobo Tan

RA-L 2026

Accurate shape reconstruction is essential for precise control and reliable operation of soft robots. Compared to sensor-based approaches, vision-based methods offer advantages in cost, simplicity, and ease of deployment. However, existing vision-based methods often rely on complex camera setups, sp

Cited by 1 Source ↗Scholar ↗

2024

ParCo: Part-Coordinating Text-to-Motion Synthesis

Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang, Chang Liu, Yi Xu +2

ECCV 2024poster

"We study a challenging task: text-to-motion synthesis, aiming to generate motions that align with textual descriptions and exhibit coordinated movements. Currently, the part-based methods introduce part partition into the motion synthesis process to achieve finer-grained generation. However, these…

Cited by 19 Source ↗PDF ↗code ↗Scholar ↗