GenPara: Enhancing the 3D Design Editing Process by Inferring Users' Regions of Interest with Text-Conditional Shape Parameters

要旨

In 3D design, specifying design objectives and visualizing complex shapes through text alone proves to be a significant challenge. Although advancements in 3D GenAI have significantly enhanced part assembly and the creation of high-quality 3D designs, many systems still to dynamically generate and edit design elements based on the shape parameters. To bridge this gap, we propose GenPara, an interactive 3D design editing system that leverages text-conditional shape parameters of part-aware 3D designs and visualizes design space within the Exploration Map and Design Versioning Tree. Additionally, among the various shape parameters generated by LLM, the system extracts and provides design outcomes within the user's regions of interest based on Bayesian inference. A user study (N = 16) revealed that GenPara enhanced the comprehension and management of designers with text-conditional shape parameters, streamlining design exploration and concretization. This improvement boosted efficiency and creativity of the 3D design process.

著者
Jiin Choi
Hanyang University, Seoul, Korea, Republic of
Seung Won Lee
Hanyang University, Seoul, Korea, Republic of
Kyung Hoon Hyun
Hanyang University, Seoul, Korea, Republic of
DOI

10.1145/3706598.3713502

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713502

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: 3D Design and Fabrication

Annex Hall F204
6 件の発表
2025-04-30 01:20:00
2025-04-30 02:50:00
日本語まとめ
読み込み中…