AI RESEARCH
Masked Language Prompting for Generative Data Augmentation in Few-shot Fashion Style Recognition
arXiv CS.CV
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ArXi:2504.19455v2 Announce Type: replace Constructing dataset for fashion style recognition is challenging due to the inherent subjectivity and ambiguity of style concepts. Recent advances in text-to-image models have facilitated generative data augmentation by synthesizing images from labeled data, yet existing methods based solely on class names or reference captions often fail to balance visual diversity and style consistency.