Creating multi-view wire art (MVWA), a static 3D sculpture with diverse interpretations from different viewpoints, is a complex task even for skilled artists. In response, we present DreamWire, an AI system enabling everyone to craft MVWA easily. Users express their vision through text prompts or scribbles, freeing them from intricate 3D wire organisation. Our approach synergises 3D B\'ezier curves, Prim's algorithm, and knowledge distillation from diffusion models or their variants (e.g., ControlNet). This blend enables the system to represent 3D wire art, ensuring spatial continuity and overcoming data scarcity. Extensive evaluation and analysis are conducted to shed insight on the inner workings of the proposed system, including the trade-off between connectivity and visual aesthetics.
@article{arxiv.2311.15421,
title = {Wired Perspectives: Multi-View Wire Art Embraces Generative AI},
author = {Zhiyu Qu and Lan Yang and Honggang Zhang and Tao Xiang and Kaiyue Pang and Yi-Zhe Song},
journal= {arXiv preprint arXiv:2311.15421},
year = {2024}
}