GHOST is a computer vision research project that performs one-shot face swapping on images and videos using deep learning. The method employs generative adversarial networks and autoencoders to transfer faces from a source to a target with high fidelity. The system takes a single reference image and can swap faces in new images or video frames, with the approach published in IEEE Xplore.