3 accepted papers
Machine unlearning, as a post-hoc processing technique, has gained widespread adoption in addressing challenges like bias mitigation and robustness enhancement. However, existing non-privacy unlearning-based solutions persist in using a binary data removal framework designed for privacy-driven motiv
Personalized text-to-image synthesis models, such as DreamBooth, have demonstrated significant potential in creating lifelike images tailored to a specific individual by fine-tuning from a limited set of face images and simple prompts. However, if misused, these model could pose a serious risk of pr…
Physical backdoor attacks are under increasing scrutiny, yet current methods often necessitate directly applying adversarial perturbations to target objects, like the attacker’s face. These approaches often pose practical challenges and compromise concealment. In this paper, we propose a stealthy, p…