Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

The locations of the fiducial facial landmark points around facial components and facial
contour capture the rigid and non-rigid facial deformations due to head movements and …

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 …

High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …

High-resolution representation learning plays an essential role in many vision problems, eg,
pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite …

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

In this work, we study the 1-bit convolutional neural networks (CNNs), of which both the
weights and activations are binary. While being efficient, the classification accuracy of the …

Deepfakes is a branch of malicious techniques that transplant a target face to the original
one in videos, resulting in serious problems such as infringement of copyright, confusion of …

In this work we propose a novel model-based deep convolutional autoencoder that
addresses the highly challenging problem of reconstructing a 3D human face from a single …

Face alignment, which fits a face model to an image and extracts the semantic meanings of
facial pixels, has been an important topic in CV community. However, most algorithms are …