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

Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D
meshes generation from a single unposed image in the wild using both2D and 3D priors. In …

We introduce GaussianAvatars a new method to create photorealistic head avatars that are
fully controllable in terms of expression pose and viewpoint. The core idea is a dynamic 3D …

Abstract We present Neural Head Avatars, a novel neural representation that explicitly
models the surface geometry and appearance of an animatable human avatar that can be …

Deep learning has significantly improved 2D image recognition. Extending into 3D may
advance many new applications including autonomous vehicles, virtual and augmented …

Abstract We present Face Swapping GAN (FSGAN) for face swapping and reenactment.
Unlike previous work, FSGAN is subject agnostic and can be applied to pairs of faces …

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 …

Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical
process of image formation. By inverting such renderer, one can think of a learning …

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