arXiv AI
Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling
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Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover scene geometries and object states, infer physical parameters, and assemble actors, objects, cameras, poses, and trajectories into a runnable physical simulation. Today this process still depends on manual tuning of visual foundation models, mesh cleanup, coordinate-frame alignment, and brittle workflow glue across visual perception tools and simulators.
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Picasso: Holistic Scene Reconstruction with Physics-Constrained Sampling
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Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation
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