Recent text-to-image diffusion models such as MidJourney and Stable Diffusion threaten to
displace many in the professional artist community. In particular, models can learn to mimic …

The success of deep learning based face recognition systems has given rise to serious
privacy concerns due to their ability to enable unauthorized tracking of users in the digital …

Few-shot-based facial recognition systems have gained increasing attention due to their
scalability and ability to work with a few face images during the model deployment phase …

Face Verification Systems (FVSes) are more and more deployed by real-world mobile
applications (apps) to verify a human's claimed identity. One popular type of FVSes is called …

The success of deep face recognition (FR) systems has raised serious privacy concerns due
to their ability to enable unauthorized tracking of users in the digital world. Previous studies …

Face recognition (FR) technologies have enabled many life-enriching applications but have
also opened doors for potential misuse. Governments, private companies, or even …

The widespread use of image acquisition technologies, along with advances in facial
recognition, has raised serious privacy concerns. Face de-identification usually refers to the …

Machine-learning models are known to be vulnerable to evasion attacks that perturb model
inputs to induce misclassifications. In this work, we identify real-world scenarios where the …

Face recognition (FR) can be abused for privacy intrusion. Governments, private companies,
or even individual attackers can collect facial images by web scraping to build an FR system …

The proliferation of images captured from millions of cameras and the advancement of facial
recognition (FR) technology have made the abuse of FR a severe privacy threat. Existing …