Systems and methods for training a machine-learning-based monocular depth estimator

Systems and methods described herein relate to training a machine-learning-based monocular depth estimator. One embodiment selects a virtual image in a virtual dataset, the virtual image having an associated ground-truth depth map; generates a set of ground-truth surface-normal vectors for pixels in the virtual image based on the ground-truth depth map; processes the virtual image using the machine-learning-based monocular depth estimator to generate a predicted depth map; generates a set of calculated surface-normal vectors for the pixels in the virtual image based on the predicted depth map; and supervises training of the machine-learning-based monocular depth estimator by computing a surface-normal loss between the set of calculated surface-normal vectors and the set of ground-truth surface-normal vectors, wherein the surface-normal loss regularizes depth predictions produced by the machine-learning-based monocular depth estimator to improve accuracy of the depth predictions as the machine-learning-based monocular depth estimator is trained.