3 papers
cs.RO2026
3D Point World Models: Point Completion Enables More Accurate Dynamics Learning
Skand Peri, Hung Nguyen, Chanho Kim +2
Learning predictive models of the world enables robotic control through planning, potentially allowing robots to improvise solutions on new tasks. However, large video-based dynami…
cs.CV2026
Learning a Particle Dynamics Model with Real-world Videos
Chanho Kim, Suhas V. Sumukh, Li Fuxin
Data-driven learning approaches for physics simulation, sometimes referred to as world models, have emerged as promising alternatives to traditional physics simulators due to their…
cs.CV2025
GS4: Generalizable Sparse Splatting Semantic SLAM
Mingqi Jiang, Chanho Kim, Chen Ziwen +1
Traditional SLAM algorithms excel at camera tracking, but typically produce incomplete and low-resolution maps that are not tightly integrated with semantics prediction. Recent wor…