arXiv AI
Sep 18

NeuSOGA3D: A Neuro-Symbolic Framework for Explainable 3D Geometric Reconstruction

NeuSOGA3D is a hybrid neuro‑symbolic framework that reconstructs 3D geometry from unorganized point clouds by combining learned perceptual priors with explicit symbolic geometric reasoning. It projects point clouds onto orthographic planes, builds symbolic implicit spline representations, and fuses them via shape‑preserving constructive solid geometry to produce a coarse visual hull. Additional detail is added through cross‑sectional decomposition and volumetric reconstruction with Partial Shape‑Preserving Splines, yielding CAD‑compatible, structurally meaningful models across all 40 ModelNet40 categories.

By Qingde Li, Qingqi Hong, Zihan Li, Jie Tian
arXiv AI
Aug 7

WorldClaw: Agentic 3D Open-World Generation at Scale

arXiv:2608. 05248v1 Announce Type: new Abstract: Generating large-scale, freely explorable 3D worlds from open-ended text remains challenging because a system must jointly maintain global spatial coherence, rich local content, and explicit assets suitable for downstream editing and reuse.

By Chunchao Guo, Jinpeng Li, Yang Li, Zilong Huang