Traditional handcrafted crowd-counting techniques in an image are currently transformed
via machine-learning and artificial-intelligence techniques into intelligent crowd-counting …

While current monocular 3D face reconstruction methods can recover fine geometric details,
they suffer several limitations. Some methods produce faces that cannot be realistically …

We present a learning framework for recovering the 3D shape, camera, and texture of an
object from a single image. The shape is represented as a deformable 3D mesh model of an …

The objective of this paper is a neural network model that controls the pose and expression
of a given face, using another face or modality (eg audio). This model can then be used for …

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 …

We present" The Relightables", a volumetric capture system for photorealistic and high
quality relightable full-body performance capture. While significant progress has been made …

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 …

We present SfSNet, an end-to-end learning framework for producing an accurate
decomposition of an unconstrained human face image into shape, reflectance and …

We propose a method for the data‐driven inference of temporal evolutions of physical
functions with deep learning. More specifically, we target fluid flow problems, and we …

Over the last years, with the advent of Generative Adversarial Networks (GANs), many face
analysis tasks have accomplished astounding performance, with applications including, but …