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

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

Generating synthetic datasets for training face recognition models is challenging because
dataset generation entails more than creating high fidelity images. It involves generating …

Image inpainting has been widely exploited in the field of computer vision and image
processing. The main purpose of image inpainting is to produce visually plausible structure …

As an emerging topic in face recognition, designing margin-based loss functions can
increase the feature margin between different classes for enhanced discriminability. More …

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

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

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 the past few years, a lot of work has been done towards reconstructing the 3D facial
structure from single images by capitalizing on the power of Deep Convolutional Neural …

In recent years, substantial progress has been achieved in learning-based reconstruction of
3D objects. At the same time, generative models were proposed that can generate highly …