3 papers
cs.AI2025
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…
cs.CV2025
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…
cs.CV2025
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…