The research project Face deidentification with Generative Deep Models (FaceGEN), strives to conduct research on deidentification technology with a particular focus on deep learning, which has recently been shown to be a highly effective tool for various computer vision and machine learning problems. Our goal is to develop deep generative models and conditional face synthesis techniques that can be used for deidentification with still images, but also with video, where multiple faces in cluttered and unconstrained scenes may appear in the data. The main tangible results of the project will be novel generative deep models and input-conditioned image synthesis techniques that are able to deidentify all parts of the facial data photo-realistically.