Aug 2026· 2 citations· ⚡ 1 influential· 55 references
Computer Science
TL;DR
The paradigm of 3D shape as code is explored, leveraging and scaling the coding ability of an LLM for 3D modeling, and Procedura, a novel 3D modeling agent framework that writes an object as a procedural assembly, a parametric program whose named parts are joined by typed, machine-checkable mates.
Abstract
Native 3D generators now recover impressive mesh geometry from a single image. However, a dense mesh stays soft where a machined object should be sharp, it carries no part decomposition, and it exposes no parameter a user could edit. To address this, we explore the paradigm of 3D shape as code, leveraging and scaling the coding ability of an LLM for 3D modeling. We introduce Procedura, a novel 3D modeling agent framework that writes an object as a procedural assembly, a parametric program whose named parts are joined by typed, machine-checkable mates. From a text prompt, the agent plans the object as an assembly graph and writes the program part by part, solving each placement from the mated frames rather than guessing it, and admitting a part only once compile, mate, and connectivity checks pass. A decoupled vision critic then refines the assembly one diagnosed fix at a time. Moreover, the same graph carries per-part materials and a simulator-validated articulation. We evaluate on P3D-Bench under its assembly judge, and with the same judge on MechBench-36, our hard-surface benchmark. On both, Procedura outperforms state-of-the-art native 3D generators and every prior 3D-code agent on judged quality, produces the sharpest edges of any method we evaluate, and is the only one whose output is an editable, part-structured program.
Current 3D generative models mostly produce a final surface: a visually strong but largely opaque mesh. Interactive 3D worlds need more than a surface. They need named parts, an assembly hierarchy, measurable constraints, local edit handles, and joints for articulation. We present Nova3D, a system that generates 3D ass...
Nimra Noor, Muhammad Bilal, A. Hussain et al.· arXiv.org· 1 citation
This work presents a training-free multi-agent system that edits existing 3D meshes directly in Blender by emulating the iterative workflow of human artists, and views this work as an exploratory step toward visual-centric agentic geometry editing in professional graphics software.
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An Agent-centric Domain-Specific Language (aDSL) and a role-specialized multi-agent system to close the gap between programmatic interfaces and reasoning strengths of LLMs, which favor semantic structure and spatial relations over fragile numeric choices.
Rui-Huan Wang, Si-Tong Wei, Jia-Qi He et al.· 2 citations
This work proposes the first end-to-end pipeline that reconstructs simulation-ready assets with accurate articulation from a single static object video input through suggestion based human-in-the-loop process, and achieves precise articulation results on partnet-mobility-v0 dataset and real objects.
Hyesung Lee, Young-Seon Lee, Kyutae Lee et al.· 1 citation
OmniMech is introduced, the first million-scale benchmark for evaluating VLMs on executable CAD generation from industrial manufacturing data, and experiments show that current VLMs and CAD-specialized models still struggle with executable program synthesis, fine-grained 3D reconstruction, and reliable enforcement of d...
Tai-Ting Lu, Run-Ze Liu, Zi-Wei Dong et al.· 0 citations
This work presents ArtLang, a framework for open-vocabulary language control of persistent reconstructed articulated assets, which represents an asset as a semantic-kinematic articulation graph and augments its surface with language features and graph-constrained motion.
Sylvia Yuan, Dan Wang, Ravi Ramamoorthi et al.· 0 citations
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