Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

We propose real-time, six degrees of freedom (6DoF), 3D face pose estimation without face
detection or landmark localization. We observe that estimating the 6DoF rigid transformation …

Recent progress in face detection (including keypoint detection), and recognition is mainly
being driven by (i) deeper convolutional neural network architectures, and (ii) larger …

This paper concerns the problem of facial landmark detection. We provide a unique new
analysis of the features produced at intermediate layers of a convolutional neural network …

We show how a simple convolutional neural network (CNN) can be trained to accurately and
robustly regress 6 degrees of freedom (6DoF) 3D head pose, directly from image intensities …

We describe a deep learning based method for estimating 3D facial expression coefficients.
Unlike previous work, our process does not relay on facial landmark detection methods as a …

Face image quality can be defined as a measure of the utility of a face image to automatic
face recognition. In this paper, we propose (and compare) two methods for learning face …

We propose a method designed to push the frontiers of unconstrained face recognition in
the wild with an emphasis on extreme out-of-plane pose variations. Existing methods either …

We present a novel approach for disentangling the content of a text image from all aspects of
its appearance. The appearance representation we derive can then be applied to new …