Zechao Li

We present a dataset of 210,000 triplets (content, style, stylized images) and an end - to - end stylization framework tailored for it, ensuring efficient style transfer.

FedMGP introduces a multi-group text-visual prompt paradigm for federated learning that effectively balances personalization and generalization , achieving state-of-the-art performance with minimal communication parameters.