Data pertaining to Chapter 3 of the PhD dissertation: "Defending Gaze Estimation against Backdoor Attacks"

This dataset accompanies the paper <em>“</em>SecureGaze: Defending Gaze Estimation Against Backdoor Attacks<em>” </em>(Chapter 3 of the PhD dissertation). This research focuses on defending deep learning-based gaze estimation models from backdoor attacks. It aims to reverse-engineer the trigger function with a generative model for reliable backdoor detection and fine-tune the identified backdoored model with the reverse-engineered trigger function. This dataset contains the codes to reproduce the results presented in the paper and the real-time video demo.