CVPR2025
Adv-CPG: A Customized Portrait Generation Framework with Facial Adversarial Attacks
Junying Wang, Hongyuan Zhang, Yuan Yuan
Abstract
Figure 1. The proposed Adv-CPG generates safe portraits that can deceive malicious face recognition systems. First row: original image. Second row: customized portrait based on the text prompt, without protection via Adv-CPG. Third row: customized portrait based on the scene text prompt, with protection via Adv-CPG. Fourth row: comparison with existing methods. The yellow number over each image: confidence score returned by Face++ when using the adversarial example for identity matching with the target (higher is better).