Sel3DCraft: Interactive Visual Prompts for User-Friendly Text-to-3D
  Generation
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.
6893117e8da45ffb0a2b253f
Nan Xiang
6893117e8da45ffb0a2b2540
Tianyi Liang
claimed_verified
2025-08-06T19:15:16.963Z
62c14609ac1b639c2d87192c
https://cdn-avatars.huggingface.co/v1/production/uploads/1656833489364-noauth.png
liangtianyi
user
tianyilt
6893117e8da45ffb0a2b2541
Haiwen Huang
6893117e8da45ffb0a2b2542
Shiqi Jiang
6893117e8da45ffb0a2b2543
Hao Huang
6893117e8da45ffb0a2b2544
Yifei Huang
6893117e8da45ffb0a2b2545
Liangyu Chen
6893117e8da45ffb0a2b2546
Changbo Wang
6893117e8da45ffb0a2b2547
Chenhui Li
Sel3DCraft: Interactive Visual Prompts for User-Friendly Text-to-3D
  Generation
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.
Sel3DCraft enhances text-to-3D generation through a dual-branch retrieval and generation system, multi-view hybrid scoring with MLLMs, and prompt-driven visual analytics, improving designer creativity.
dual-branch structure retrieval generation multi-view hybrid scoring MLLMs high-level metrics visual analytics prompt-driven