AI RESEARCH
FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing
arXiv CS.CV
•
ArXi:2604.26186v1 Announce Type: new Fashion AI systems routinely encode the aesthetic logic of specific houses, editors, and historical moments without disclosing it. We present FASH-iCNN, a multimodal system trained on 87,547 Vogue runway images across 15 fashion houses spanning 1991-2024 that makes this cultural logic inspectable. Given a photograph of a garment, the system recovers which house produced it, which era it belongs to, and which color tradition it reflects.