PhD student, Nanjing University of Science and Technology
1 paper at NeurIPS 2025
We propose OmniGaze, a semi-supervised learning framework, which utilizes large-scale unlabeled data and reward-driven pseudo-labeling strategy to effectively generalize gaze estimation in the wild.
