5 papers · 1 filter
CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets
Jihun Park, Kyoungmin Lee, Jongmin Gim +6
Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foundational capability for mode…
Infinite-Story: A Training-Free Consistent Text-to-Image Generation
Jihun Park, Kyoungmin Lee, Jongmin Gim +7
We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoreg…
A Training-Free Style-Personalization via SVD-Based Feature Decomposition
Kyoungmin Lee, Jihun Park, Jongmin Gim +4
We present a training-free framework for style-personalized image generation that operates during inference using a scale-wise autoregressive model. Our method generates a stylized…
A Training-Free Style-aligned Image Generation with Scale-wise Autoregressive Model
Jihun Park, Jongmin Gim, Kyoungmin Lee +5
We present a training-free style-aligned image generation method that leverages a scale-wise autoregressive model. While large-scale text-to-image (T2I) models, particularly diffus…
Style-Editor: Text-driven object-centric style editing
Jihun Park, Jongmin Gim, Kyoungmin Lee +2
We present Text-driven object-centric style editing model named Style-Editor, a novel method that guides style editing at an object-centric level using textual inputs. The core of…