Point-E: A system for generating 3D point clouds from complex prompts
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arXiv:2608.20448v1 Announce Type: cross Abstract: Digital 3D objects used in games and animation are often required to be compositional; that is, decomposed into semantically meaningful parts. Recent...
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.
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.
arXiv:2601. 18252v2 Announce Type: replace-cross Abstract: Wireframe parsing aims to recover line segments and their junctions to form a structured geometric representation useful for downstream tasks such as Simultaneous Localization and Mapping (SLAM).
arXiv:2604.26943v2 Announce Type: replace Abstract: We introduce ProcFunc, a library for Blender-based procedural 3D generation in Python. ProcFunc provides a library of easy-to-use Python functions,...
Researchers developed an automated framework that helps AI models generate CAD programs more accurately and efficiently.