Systems, methods and media for deep shape prediction

A computer-implemented method of training a neural network for facial reconstruction comprising:

• collecting a synthetic dataset of non-existing 3D head scans produced by randomly sampling a 3D morphable model and rendered under diverse lighting conditions, camera settings, and pose conditions, wherein the diverse lighting conditions comprise rendering using high dynamic range images (HDRIs);
• combining each feature of each 3D head scan with a projected weight to create a modified set of 3D head scans;
• measuring an error between the projected weight and an actual weight;
• adjusting neural network weights for the error and repeating the measuring and adjusting until the error converges or is near or at zero;
• training the neural network using the modified set of 3D head scans;
• and
• inputting a real digital facial image into the neural network for the facial reconstruction.