5 papers
APT: Anchor-aligned Perturbations for Tamper Localization in Fully Regenerated Images
Suhyeon Ha, Woo Jae Kim, Joonsung Jeon +2
Proactive tamper localization embeds an imperceptible signal into an image prior to distribution, enabling pixel-level manipulation detection. Existing methods assume a spliced (SP…
RoME: Robust Mixture of Low-Rank Experts against Multiple Adversarial Perturbations
Woo Jae Kim, Kyle Min, Suhyeon Ha +2
Multi-perturbation adversarial training (MAT) aims to achieve robustness against multiple perturbations but suffers from robustness trade-offs between different threats. T…
No Caption, No Problem: Caption-Free Membership Inference via Model-Fitted Embeddings
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha +2
Latent diffusion models have achieved remarkable success in high-fidelity text-to-image generation, but their tendency to memorize training data raises critical privacy and intelle…
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha +2
The outstanding capability of diffusion models in generating high-quality images poses significant threats when misused by adversaries. In particular, we assume malicious adversari…
UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and UnFavOrable Sets
Youngju Na, Woo Jae Kim, Kyu Beom Han +2
Generalizable neural implicit surface reconstruction aims to obtain an accurate underlying geometry given a limited number of multi-view images from unseen scenes. However, existin…