However, their utility is limited by their entanglement with respect to different visual attributes.

We introduce a new approach, Generative mOdel finetun-ing with Reward-driven Sample selection (GORS), to boost the compositional text-to-image generation abilities of pretrained text-to-image models.

That which we call a rose by any other name would smell as sweet."

In this work, we present MuDI, a novel framework that enables multi-subject personalization by effectively decoupling identities from multiple subjects.

We curate 62 scenarios encompassing these aspects and evaluate 26 state-of-the-art text-to-image models on this benchmark.

We curate 62 scenarios encompassing these aspects and evaluate 26 state-of-the-art text-to-image models on this benchmark.

Well-designed prompts can guide text-to-image models to generate amazing images.

Large-scale pre-trained generative models are taking the world by storm, due to their abilities in generating creative content.