3 papers
cs.CV2026
DeformMaster: An Interactive Physics-Neural World Model for Deformable Objects from Videos
Can Li, Zhoujian Li, Ren Li +4
World models for deformable objects should recover not only geometry and appearance, but also underlying physical dynamics, interaction grounding, and material behavior. Learning s…
cs.CV2026
FTSplat: Feed-forward Triangle Splatting Network
Xiong Jinlin, Li Can, Shen Jiawei +3
High-fidelity three-dimensional (3D) reconstruction is essential for robotics and simulation. While Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) achieve impressiv…
cs.CV2026
Gaussian Sequences with Multi-Scale Dynamics for 4D Reconstruction from Monocular Casual Videos
Can Li, Jie Gu, Jingmin Chen +2
Understanding dynamic scenes from casual videos is critical for scalable robot learning, yet four-dimensional (4D) reconstruction under strictly monocular settings remains highly i…