Sel3DCraft: Interactive Visual Prompts for User-Friendly Text-to-3D
  Generation
Authors: name: Nan Xiang; name: Tianyi Liang; name: Haiwen Huang; name: Shiqi Jiang; name: Hao Huang; name: Yifei Huang; name: Liangyu Chen; name: Changbo Wang; name: Chenhui Li
Published: 2025-08-01 08:36:15

Abstract: Text-to-3D (T23D) generation has transformed digital content creation, yet
remains bottlenecked by blind trial-and-error prompting processes that yield
unpredictable results. While visual prompt engineering has advanced in
text-to-image domains, its application to 3D generation presents unique
challenges requiring multi-view consistency evaluation and spatial
understanding. We present Sel3DCraft, a visual prompt engineering system for
T23D that transforms unstructured exploration into a guided visual process. Our
approach introduces three key innovations: a dual-branch structure combining
retrieval and generation for diverse candidate exploration; a multi-view hybrid
scoring approach that leverages MLLMs with innovative high-level metrics to
assess 3D models with human-expert consistency; and a prompt-driven visual
analytics suite that enables intuitive defect identification and refinement.
Extensive testing and user studies demonstrate that Sel3DCraft surpasses other
T23D systems in supporting creativity for designers.