NeoWorld-3: From Pixels to Code-Defined Physical Worlds
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arXiv:2610.27690v1 Announce Type: new Abstract: Simulation-ready world reconstruction demands physical interactivity beyond visual realism, which existing black-box 3D generation fails to deliver. We...
arXiv:2608.24212v1 Announce Type: new Abstract: The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual obse...
The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual observations into simulation-ready scenes remains cha...
WorldMirror is a real‑to‑sim framework that builds interactive digital twins from real‑world robot demonstrations by iteratively refining an executable world program. A coding agent decomposes the observed scene, plans reconstruction steps, and coordinates image and 3D generation tools, using verification feedback to correct errors. The resulting camera‑pose‑anchored scene representation preserves spatial relationships and enables physically consistent interaction and trajectory replay, as shown on the DROID dataset.
arXiv:2606. 01057v1 Announce Type: cross Abstract: Procedural 3D modeling through code is emerging as a versatile paradigm, offering deterministic, engine-ready, and precisely editable assets that neural 3D generators inherently lack.
The paper surveys 3D generation techniques tailored for embodied AI and robotics, emphasizing that beyond visual realism, generated content must include kinematic structure, material properties, and interaction capabilities. It categorizes the literature into three roles: Data Generator, Simulation Environments, and Sim2Real Bridge, each addressing different needs in training and deployment. The survey highlights a shift toward interaction readiness and identifies key bottlenecks such as limited physical annotations, quality gaps, fragmented evaluation, and the sim‑to‑real divide.