In this paper, we propose a novel deep convolutional network (DCN) that achieves
outstanding performance on FDDB, PASCAL Face, and AFW. Specifically, our method …

We propose a deep convolutional neural network (CNN) for face detection leveraging on
facial attributes based supervision. We observe a phenomenon that part detectors emerge …

Abstract Deep Convolutional Neural Networks (CNNs) achieve substantial improvements in
face detection in the wild. Classical CNN-based face detection methods simply stack …

Face detection is one of the most studied topics in the computer vision community. Much of
the progresses have been made by the availability of face detection benchmark datasets …

In real-world face detection, large visual variations, such as those due to pose, expression,
and lighting, demand an advanced discriminative model to accurately differentiate faces …

This paper presents a real-time face detector, named Single Shot Scale-invariant Face
Detector (S3FD), which performs superiorly on various scales of faces with a single deep …

Face detection is a well-explored problem. Many challenges on face detectors like extreme
pose, illumination, low resolution and small scales are studied in the previous work …

Face detection has achieved great success using the region-based methods. In this report,
we propose a region-based face detector applying deep networks in a fully convolutional …

Face detection has achieved significant progress in recent years. However, high
performance face detection still remains a very challenging problem, especially when there …

Most facial recognition and face analysis systems start with facial detection. Early
techniques, such as Haar cascades and histograms of directed gradients, mainly rely on …