Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

Humans, being highly social creatures, rely heavily on the ability to perceive what others are
doing and to infer from gestures and expressions what others may be intending to do. These …

We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose
and shape. Though substantial progress has been made in estimating 3D human motion …

With the recent surge in popularity of AR/VR applications, realistic and accurate control of
3D full-body avatars has become a highly demanded feature. A particular challenge is that …

We present a unified perspective on tackling various human-centric video tasks by learning
human motion representations from large-scale and heterogeneous data resources …

Human pose forecasting is a complex structured-data sequence-modelling task, which has
received increasing attention, also due to numerous potential applications. Research has …

There is compelling evidence that the human cerebellum is engaged in a wide array of
motor and cognitive tasks. A fundamental question centers on whether the cerebellum is …

Large datasets are the cornerstone of recent advances in computer vision using deep
learning. In contrast, existing human motion capture (mocap) datasets are small and the …

Abstract Today's Mixed Reality head-mounted displays track the user's head pose in world
space as well as the user's hands for interaction in both Augmented Reality and Virtual …

This paper tackles the problem of human motion prediction, consisting in forecasting future
body poses from historically observed sequences. State-of-the-art approaches provide good …