5 papers
Causal-Tune: Mining Causal Factors from Vision Foundation Models for Domain Generalized Semantic Segmentation
Yin Zhang, Yongqiang Zhang, Yaoyue Zheng +2
Fine-tuning Vision Foundation Models (VFMs) with a small number of parameters has shown remarkable performance in Domain Generalized Semantic Segmentation (DGSS). Most existing wor…
An h-space Based Adversarial Attack for Protection Against Few-shot Personalization
Xide Xu, Sandesh Kamath, Muhammad Atif Butt +1
The versatility of diffusion models in generating customized images from few samples raises significant privacy concerns, particularly regarding unauthorized modifications of priva…
Leveraging Semantic Attribute Binding for Free-Lunch Color Control in Diffusion Models
Héctor Laria, Alexandra Gomez-Villa, Jiang Qin +5
Recent advances in text-to-image (T2I) diffusion models have enabled remarkable control over various attributes, yet precise color specification remains a fundamental challenge. Ex…
Multi-label out-of-distribution detection via evidential learning
Eduardo Aguilar, Bogdan Raducanu, Petia Radeva
A crucial requirement for machine learning algorithms is not only to perform well, but also to show robustness and adaptability when encountering novel scenarios. One way to achiev…
Privacy Protection in Personalized Diffusion Models via Targeted Cross-Attention Adversarial Attack
Xide Xu, Muhammad Atif Butt, Sandesh Kamath +1
The growing demand for customized visual content has led to the rise of personalized text-to-image (T2I) diffusion models. Despite their remarkable potential, they pose significant…