Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

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 …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

Abstract Conditional Generative Adversarial Networks (GANs) for cross-domain image-to-
image translation have made much progress recently. Depending on the task complexity …

In this paper we propose a novel abstraction-aware sketch-based image retrieval framework
capable of handling sketch abstraction at varied levels. Prior works had mainly focused on …

Recent deep image-to-image translation techniques allow fast generation of face images
from freehand sketches. However, existing solutions tend to overfit to sketches, thus …

This paper presents a highly efficient, very accurate regression approach for face alignment.
Our approach has two novel components: a set of local binary features, and a locality …

In many computer vision systems, the same object can be observed at varying viewpoints or
even by different sensors, which brings in the challenging demand for recognizing objects …

Having a lot of labeled data is always a problem in machine learning issues. Even by
collecting lots of data hardly, shift in data distribution might emerge because of differences in …

In recent years, heterogeneous face biometrics has attracted more attentions in the face
recognition community. After published in 2009, the HFB database [7] has been applied by …