Generalization to out-of-distribution (OOD) data is a capability natural to humans yet
challenging for machines to reproduce. This is because most learning algorithms strongly …

Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …

As 3D facial avatars become more widely used for communication, it is critical that they
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …

Face mask detection had seen significant progress in the domains of Image processing and
Computer vision, since the rise of the Covid-19 pandemic. Many face detection models have …

The current spike of hyper-realistic faces artificially generated using deepfakes calls for
media forensics solutions that are tailored to video streams and work reliably with a low false …

In this paper, we contribute a new million-scale face benchmark containing noisy 4M
identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) …

'Vital reading. This is the book on artificial intelligence we need right now.'Mike Krieger,
cofounder of Instagram Artificial intelligence is rapidly dominating every aspect of our …

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 …

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

Recently, deep learning based 3D face reconstruction methods have shown promising
results in both quality and efficiency. However, training deep neural networks typically …