CVPR2025
AIpparel: A Multimodal Foundation Model for Digital Garments
Kiyohiro Nakayama, Jan Ackermann, Timur Levent Kesdogan, Yang Zheng, Maria Korosteleva, Olga Sorkine-Hornung, Leonidas J. Guibas, Guandao Yang, Gordon Wetzstein
Abstract
Figure 1 . AIpparel. We present a multimodal foundation model for digital garments trained by fine-tuning a large multimodal model on a custom sewing pattern dataset using a novel tokenization scheme for these patterns. AIpparel generates complex, diverse, high-quality sewing patterns based on multimodal inputs, such as text and images, and it unlocks new applications such as language-instructed sewing pattern editing. The generated sewing patterns can be directly used to simulate the corresponding 3D garments.