arXiv cs.CV
· Papers
DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation
arXiv:2606.23950v1 Announce Type: new Abstract: Subject-driven image generation faces an "Identity-Diversity Paradox", where strong identity preservation often leads to rigid and low-diversity outputs. We propose a post-training framework called DivRL that jointly optimizes identity consistency and structural diversity