4 papers
DIA: The Adversarial Exposure of Deterministic Inversion in Diffusion Models
Seunghoo Hong, Geonho Son, Juhun Lee +1
Diffusion models have shown to be strong representation learners, showcasing state-of-the-art performance across multiple domains. Aside from accelerated sampling, DDIM also enable…
Fitting Image Diffusion Models on Video Datasets
Juhun Lee, Simon S. Woo
Image diffusion models are trained on independently sampled static images. While this is the bedrock task protocol in generative modeling, capturing the temporal world through the…
PromptFlare: Prompt-Generalized Defense via Cross-Attention Decoy in Diffusion-Based Inpainting
Hohyun Na, Seunghoo Hong, Simon S. Woo
The success of diffusion models has enabled effortless, high-quality image modifications that precisely align with users' intentions, thereby raising concerns about their potential…
Translation of Text Embedding via Delta Vector to Suppress Strongly Entangled Content in Text-to-Image Diffusion Models
Eunseo Koh, Seunghoo Hong, Tae-Young Kim +2
Text-to-Image (T2I) diffusion models have made significant progress in generating diverse high-quality images from textual prompts. However, these models still face challenges in s…