6 papers · 1 filter
Anchor-Regularized Adaptation for Generalizable AI-Generated Image Detection with DINOv3
Hyeongjun Choi, Juhun Lee, Davide Cozzolino +2
Recent works in AI-generated image detection have shown that careful training data alignment can improve generalization by removing spurious correlations. However, linear probes on…
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…
Continuous Memory Representation for Anomaly Detection
Joo Chan Lee, Taejune Kim, Eunbyung Park +2
There have been significant advancements in anomaly detection in an unsupervised manner, where only normal images are available for training. Several recent methods aim to detect a…
Disrupting Diffusion-based Inpainters with Semantic Digression
Geonho Son, Juhun Lee, Simon S. Woo
The fabrication of visual misinformation on the web and social media has increased exponentially with the advent of foundational text-to-image diffusion models. Namely, Stable Diff…