Appearance debiased gaze estimation via stochastic subject-wise adversarial learning

Suneung Kim, Woo-Jeoung Nam, Seong-Whan Lee

Abstract: Highlights•We suggest adversarial training for gaze estimation to generalize facial appearances.•We propose a stochastic strategy for subject-wise training to improve generalization.•Our framework achieves state-of-the-art performance on the MPIIFaceGaze and Eyediap.