Abstract: Example embodiments relate to estimating depth information based on iris size. A computing system may obtain an image depicting a person and determine a facial mesh for a face of the person based on features of the face. In some instances, the facial mesh includes a combination of facial landmarks and eye landmarks. As such, the computing system may estimate an iris pixel dimension of an eye based on the eye landmarks of the facial mesh and estimate a distance of the eye of the face relative to the camera based on the iris pixel dimension, a mean value iris dimension, and an intrinsic matrix of the camera. The computing system may further modify the image based on the estimated distance.

Abstract: Example embodiments relate to estimating depth information based on iris size. A computing system may obtain an image depicting a person and determine a facial mesh for a face of the person based on features of the face. In some instances, the facial mesh includes a combination of facial landmarks and eye landmarks. As such, the computing system may estimate an iris pixel dimension of an eye based on the eye landmarks of the facial mesh and estimate a distance of the eye of the face relative to the camera based on the iris pixel dimension, a mean value iris dimension, and an intrinsic matrix of the camera. The computing system may further modify the image based on the estimated distance.

Abstract: Example embodiments relate to estimating depth information based on iris size. A computing system may obtain an image depicting a person and determine a facial mesh for a face of the person based on features of the face. In some instances, the facial mesh includes a combination of facial landmarks and eye landmarks. As such, the computing system may estimate an iris pixel dimension of an eye based on the eye landmarks of the facial mesh and estimate a distance of the eye of the face relative to the camera based on the iris pixel dimension, a mean value iris dimension, and an intrinsic matrix of the camera. The computing system may further modify the image based on the estimated distance.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network model to predict mesh vertices corresponding to a three-dimensional surface geometry of an object depicted in an image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network model to predict mesh vertices corresponding to a three-dimensional surface geometry of an object depicted in an image.