Photorealistic rendering and reposing of humans is important for enabling augmented reality
experiences. We propose a novel framework to reconstruct the human and the scene that …

We propose a direct, regression-based approach to 2D human pose estimation from single
images. We formulate the problem as a sequence prediction task, which we solve using a …

Modeling and rendering photorealistic avatars is of crucial importance in many applications.
Existing methods that build a 3D avatar from visual observations, however, struggle to …

We propose an unsupervised method for 3D geometry-aware representation learning of
articulated objects, in which no image-pose pairs or foreground masks are used for training …

Facial expression and hand motions are necessary to express our emotions and interact
with the world. Nevertheless, most of the 3D human avatars modeled from a casually …

With the recent vision of Industry 5.0, the cognitive capability of robots plays a crucial role in
advancing proactive human–robot collaborative assembly. As a basis of the mutual …

The Internet of Things and multimedia devices generate a tremendous amount of data. The
transfer of this data to the cloud is a challenging problem because of the congestion at the …

Human pose estimation aims to accurately estimate a wide variety of human poses.
However, existing datasets often follow a long-tailed distribution that unusual poses only …

In this paper, we dive into sign language recognition, focusing on the recognition of isolated
signs. The task is defined as a classification problem, where a sequence of frames (ie …

Pose estimation can be used to analyse the behaviour of livestock, hence offering valuable
insights into the physiological state of the livestock. Despite impressive progress in …