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

Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …

Data augmentation has been widely used to improve generalizability of machine learning
models. However, comparatively little work studies data augmentation for graphs. This is …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

While the quality of GAN image synthesis has improved tremendously in recent years, our
ability to control and condition the output is still limited. Focusing on StyleGAN, we introduce …

Emerging Internet of Things (IoT) applications, such as cashier-less shopping, mobile ads
targeting, and geo-based augmented reality (AR), are expected to bring us much more …

In recent years, convolutional neural networks have proven to be a highly efficient approach
for face recognition. In this paper, we develop such a framework to learn a robust face …

Deep generative models have become an emerging topic in various research areas like
computer vision and signal processing. These models allow synthesizing realistic data …

To fully support the emerging location-aware applications, location information with meter-
level resolution (or even higher) is required anytime and anywhere. Unfortunately, most of …

Abstract COVID-19 (Coronavirus) went through a rapid escalation until it became a
pandemic disease. The normal and manual medical infection discovery may take few days …