This repository implements Apple’s SimGAN paper, a generative adversarial network approach for simulated unsupervised learning. The model refines synthetic images to better match real-world distributions without paired training data. The implementation uses Keras with TensorFlow backend and focuses on gaze estimation applications using the SynthesEyes and MPIIGaze datasets.