Filigree art, which represents typical intricate metalwork, has been captivating audiences worldwide with its delicate lace-like patterns and interwoven metal wires' refined aesthetics. Particularly, Chinese Intangible Cultural Heritage filigree craftsmanship has a unique aesthetic value in fine patterns and complex three-dimensional shapes. However, designing and creating filigree artworks is a labor-intensive and technically complex task and often requires extensive training and a deep understanding of the craft, which limits its design aesthetic and cultural continuity. Aiming to overcome these challenges, this study proposes an artificial intelligence (AI)-aided method that uses AI-generated content (AIGC) technology to accelerate the visualization process of this time-consuming and intricate craft by investigating the role of AI in craft design. First, a comprehensive study of filigree art culture is conducted to identify more than ten historic filigree techniques to obtain AI opportunities. Then, an AI-powered framework called AIFiligree is developed by optimizing culture-based labels and training parameters, enabling the generation of highly authentic fine filigree structures. Further, user workflows are introduced to support diverse design scenarios. Through user studies involving 22 filigree experts and 16 designers, we finally gained insights into AI's opportunities and challenges in cultural learning, expression, and design.
https://dl.acm.org/doi/10.1145/3706598.3713281
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)