Few-shot image generation via style adaptation and content preservation

• Main Authors: He, Xiaosheng, Yang, Fan, Liu, Fayao, Lin, Guosheng
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2025
• Subjects: Computer and Information Science; Few-shot learning; Generative model
• Online Access: https://hdl.handle.net/10356/182764
• Institution: Nanyang Technological University

Training a generative model with limited data (e.g., 10) is a very challenging task. Many works propose to fine-tune a pretrained GAN model. However, this can easily result in overfitting. In other words, they manage to adapt the style but fail to preserve the content, where style denotes the specif...