Proc3D: Procedural 3D Generation and Parametric Editing of 3D Shapes with Large Language Models
Fadlullah Raji, Stefano Petrangeli, Matheus Gadelha, Yu Shen, Uttaran Bhattacharya, Gang Wu

TL;DR
Proc3D introduces a novel system for generating and editing 3D models using large language models, enabling real-time, text-driven modifications with a compact graph representation that enhances efficiency and accuracy.
Contribution
The paper presents Proc3D, a system that creates editable 3D models with real-time natural language editing capabilities using a new procedural graph representation and large language models.
Findings
Achieves over 400x speedup in editing compared to traditional methods.
Improves ULIP scores by 28%, indicating better text-model alignment.
Enables intuitive, real-time parametric adjustments and text-based editing of 3D models.
Abstract
Generating 3D models has traditionally been a complex task requiring specialized expertise. While recent advances in generative AI have sought to automate this process, existing methods produce non-editable representation, such as meshes or point clouds, limiting their adaptability for iterative design. In this paper, we introduce Proc3D, a system designed to generate editable 3D models while enabling real-time modifications. At its core, Proc3D introduces procedural compact graph (PCG), a graph representation of 3D models, that encodes the algorithmic rules and structures necessary for generating the model. This representation exposes key parameters, allowing intuitive manual adjustments via sliders and checkboxes, as well as real-time, automated modifications through natural language prompts using Large Language Models (LLMs). We demonstrate Proc3D's capabilities using two generative…
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Taxonomy
Topics3D Shape Modeling and Analysis · Interactive and Immersive Displays · Innovations in Concrete and Construction Materials
