Face detection has been one of the most studied topics in the computer vision literature. In
this technical report, we survey the recent advances in face detection for the past decade …

Boosting is a class of machine learning methods based on the idea that a combination of
simple classifiers (obtained by a weak learner) can perform better than any of the simple …

Predicting face attributes in the wild is challenging due to complex face variations. We
propose a novel deep learning framework for attribute prediction in the wild. It cascades two …

In this paper we consider the problem of multi-view face detection. While there has been
significant research on this problem, current state-of-the-art approaches for this task require …

Face detection is one of the most studied topics in computer vision literature, not only
because of the challenging nature of face as an object, but also due to the countless …

We present a method for detecting 3D objects using multi-modalities. While it is generic, we
demonstrate it on the combination of an image and a dense depth map which give …

We present a method for real-time 3D object instance detection that does not require a time-
consuming training stage, and can handle untextured objects. At its core, our approach is a …

Detection and tracking of humans in video streams is important for many applications. We
present an approach to automatically detect and track multiple, possibly partially occluded …

In the year 1999 the world population reached 6 billion, doubling the previous census
estimate of 1960. Recently, the United States Census Bureau issued a revised forecast for …

Large pose variations remain to be a challenge that confronts real-word face detection. We
propose a new cascaded Convolutional Neural Network, dubbed the name Supervised …