FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions

arXiv:2404.16336v1 Announce Type: new
Abstract: The unique artistic style is crucial to artists' occupational competitiveness, yet prevailing Art Commission Platforms rarely support style-based retrieval. Meanwhile, the fast-growing generative AI techniques aggravate artists' concerns about releasing personal artworks to public platforms. To achieve artistic style-based retrieval without exposing personal artworks, we propose FedStyle, a style-based federated learning crowdsourcing framework. It allows artists to train local style models and share model parameters rather than artworks for collaboration. However, most artists possess a …

abstract ai techniques art artists artworks arxiv commission concerns crowdsourcing cs.cv cs.lg federated learning framework generative platforms public retrieval style support type unique