5 papers
Custom Forcing: Training-Free Subject Customization for Autoregressive Video Generation
Yunseung Ok, Hyunsoo Kim, Minseo Kim +1
Autoregressive video models can generate minute-long videos in real time, but they produce generic subjects from text rather than specific subjects from user-provided images. Exist…
Self-Improving Diffusion Classifiers with Minority Preference Optimization
Hyunsoo Kim, Jungmyung Wi, Soobin Um +2
Prior studies have demonstrated that diffusion classifiers achieve robust zero-shot classification performance. However, their effectiveness is strongly tied to the pretraining dat…
Correlation-Weighted Multi-Reward Optimization for Compositional Generation
Jungmyung Wi, Hyunsoo Kim, Donghyun Kim
Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. Models often struggle to satisfy…
When Model Knowledge meets Diffusion Model: Diffusion-assisted Data-free Image Synthesis with Alignment of Domain and Class
Yujin Kim, Hyunsoo Kim, Hyunwoo J. Kim +1
Open-source pre-trained models hold great potential for diverse applications, but their utility declines when their training data is unavailable. Data-Free Image Synthesis (DFIS) a…
Difference Inversion: Interpolate and Isolate the Difference with Token Consistency for Image Analogy Generation
Hyunsoo Kim, Donghyun Kim, Suhyun Kim
How can we generate an image B' that satisfies A:A'::B:B', given the input images A,A' and B? Recent works have tackled this challenge through approaches like visual in-context lea…