Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

Face recognition technology is a biometric technology, which is based on the identification
of facial features of a person. People collect the face images, and the recognition equipment …

How should we integrate representations from complementary sensors for autonomous
driving? Geometry-based fusion has shown promise for perception (eg, object detection …

Although generative adversarial networks (GANs) have made significant progress in face
synthesis, there lacks enough understanding of what GANs have learned in the latent …

Despite the recent advance of Generative Adversarial Networks (GANs) in high-fidelity
image synthesis, there lacks enough understanding of how GANs are able to map a latent …

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

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

We propose an approach for face image generation of virtual people with disentangled,
precisely-controllable latent representations for identity of non-existing people, expression …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

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