WCCA-AK: A Multimodal Dataset of Andre Kim's Fashion Legacy for AI-Driven Cultural Heritage Research

Seongyeon Oh, Soyoung Lee, Hyeon Seong Jeong, Sangwoo Jo, Jin Young Kim, Yeonseo Choi, YoungJoon Yoo, Taehoon Kim; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2025, pp. 4495-4500

Abstract

Preserving an artist's legacy in the digital era presents a signifcant challenge. We introduce WCCA-AK, a multimodal collection derived from the work of Andre Kim, a South Korean fashion designer. The dataset targets computer vision and AI research on cultural heritage tasks, supporting multimodal deep learning, 3D reconstruction, generative models, and pattern recognition. Grounded in a single-designer case study, the dataset supports the Workshop on Cultural Continuity of Artists (WCCA). It enables research applications while informing ethical discussions on digitizing artistic legacies.

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[bibtex]
@InProceedings{Oh_2025_ICCV, author = {Oh, Seongyeon and Lee, Soyoung and Jeong, Hyeon Seong and Jo, Sangwoo and Kim, Jin Young and Choi, Yeonseo and Yoo, YoungJoon and Kim, Taehoon}, title = {WCCA-AK: A Multimodal Dataset of Andre Kim's Fashion Legacy for AI-Driven Cultural Heritage Research}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2025}, pages = {4495-4500} }