Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …

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 …

In this paper, we present a new face detection scheme using deep learning and achieve the
state-of-the-art detection performance on the well-known FDDB face detection benchmark …

Although tremendous strides have been made in face detection, one of the remaining open
challenges is to achieve real-time speed on the CPU as well as maintain high performance …

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 new state-of-the-art approach for face detection. The key idea is to combine
face alignment with detection, observing that aligned face shapes provide better features for …

Real data are often collected from multiple channels or comprised of different
representations (ie, views). Multi-view learning provides an elegant way to analyze the multi …

Face detection has drawn much attention in recent decades since the seminal work by Viola
and Jones. While many subsequences have improved the work with more powerful learning …

Despite the maturity of face detection research, it remains difficult to compare different
algorithms for face detection. This is partly due to the lack of common evaluation schemes …

We present a novel method for generic visual categorization: the problem of identifying the
object content of natural images while generalizing across variations inherent to the object …