DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation

Qian Wang, Zhenyu Li, Abdelrahman Eldesokey, Peter Wonka

Abstract

A post-training framework for subject-driven image generation that optimizes structural diversity and identity consistency together, treating identity preservation as a feasibility constraint rather than a competing objective so both can improve jointly.