Abstract: One embodiment provides a method for face liveness detection. The method comprises receiving a first image comprising a face of a user, determining one or more two-dimensional (2D) facial landmark points based on the first image, and determining a three-dimensional (3D) pose of the face in the first image based on the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points in a 3D face model for the user. The method further comprises determining a homography mapping between the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points that are perspectively projected based on the 3D pose, and determining liveness of the face in the first image based on the homography mapping.

Abstract: Methods, devices, and computer-readable media for incremental learning in image classification and/or object detection. A method for incremental learning includes identifying, for a model for object detection or classification, a first set of object classes the model is trained to detect or classify and adapting the model for use with a second set of object classes different from the first set of object classes to generate an adapted model. The method further includes retaining detection or classification performance on the first set of object classes in the adapted model by performing a knowledge distillation process for the model; and using the adapted model to detect or classify one or more objects from the first set of object classes and one or more objects from the second set of object classes.

Abstract: One embodiment provides a method for face liveness detection. The method comprises receiving a first image comprising a face of a user, determining one or more two-dimensional (2D) facial landmark points based on the first image, and determining a three-dimensional (3D) pose of the face in the first image based on the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points in a 3D face model for the user. The method further comprises determining a homography mapping between the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points that are perspectively projected based on the 3D pose, and determining liveness of the face in the first image based on the homography mapping.