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 …

Recently, a lot of attention has been focused on the incorporation of 3D data into face
analysis and its applications. Despite providing a more accurate representation of the face …

Existing methods of 3D dthus limiting the scope of their practical applications. In this paper,
we propose a novel regression framework which makes a balance among speed, accuracy …

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient 2D face alignment and 3D face reconstruction in-the-wild remain an open …

We motivate and present feature selective anchor-free (FSAF) module, a simple and
effective building block for single-shot object detectors. It can be plugged into single-shot …

We propose a straightforward method that simultaneously reconstructs the 3D facial
structure and provides dense alignment. To achieve this, we design a 2D representation …

We present a new loss function, namely Wing loss, for robust facial landmark localisation
with Convolutional Neural Networks (CNNs). We first compare and analyse different loss …

Neural architecture search (NAS) has shown great potential in automating the manual
process of designing a good CNN architecture for image classification. In this paper, we …

Recent learning-based approaches, in which models are trained by single-view images
have shown promising results for monocular 3D face reconstruction, but they suffer from the …

We motivate and present Ring loss, a simple and elegant feature normalization approach for
deep networks designed to augment standard loss functions such as Softmax. We argue that …