4 papers
APT: Adaptive Personalized Training for Diffusion Models with Limited Data
JungWoo Chae, Jiyoon Kim, JaeWoong Choi +2
Personalizing diffusion models using limited data presents significant challenges, including overfitting, loss of prior knowledge, and degradation of text alignment. Overfitting le…
Parallel Rescaling: Rebalancing Consistency Guidance for Personalized Diffusion Models
JungWoo Chae, Jiyoon Kim, Sangheum Hwang
Personalizing diffusion models to specific users or concepts remains challenging, particularly when only a few reference images are available. Existing methods such as DreamBooth a…
Semantic Image Synthesis with Unconditional Generator
Jungwoo Chae, Hyunin Cho, Sooyeon Go +2
Semantic image synthesis (SIS) aims to generate realistic images that match given semantic masks. Despite recent advances allowing high-quality results and precise spatial control,…
GTA: Guided Transfer of Spatial Attention from Object-Centric Representations
SeokHyun Seo, Jinwoo Hong, JungWoo Chae +2
Utilizing well-trained representations in transfer learning often results in superior performance and faster convergence compared to training from scratch. However, even if such go…