3 papers
cs.CV2026
BendTwin: Robust Dense-to-Sparse Physical Reconstruction with Bending-Aware Differentiable Spring-Mass Models
Yixiong Jing, Qi Wang, Lin Chen +6
Reconstructing objects with mechanical properties from video observations enables physically consistent dynamic prediction, benefiting robotics planning and interaction. Existing s…
cs.RO2026
PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN
Yixiong Jing, Xingyuan Chen, Guangming Wang +3
Physics-based digital twins aim to predict the dynamics of real-world objects under interaction, enabling real-to-sim-to-real applications in robotics. Current approaches reconstru…
cs.CV2025
InfraDiffusion: zero-shot depth map restoration with diffusion models and prompted segmentation from sparse infrastructure point clouds
Yixiong Jing, Cheng Zhang, Haibing Wu +3
Point clouds are widely used for infrastructure monitoring by providing geometric information, where segmentation is required for downstream tasks such as defect detection. Existin…