Gestures that accompany speech are an essential part of natural and efficient embodied
human communication. The automatic generation of such co‐speech gestures is a long …

This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …

We introduce a novel sequential modeling approach which enables learning a Large Vision
Model (LVM) without making use of any linguistic data. To do this we define a common …

Driving 3D characters to dance following a piece of music is highly challenging due to the
spatial constraints applied to poses by choreography norms. In addition, the generated …

Synthesizing graceful and life-like behaviors for physically simulated characters has been a
fundamental challenge in computer animation. Data-driven methods that leverage motion …

Learning the spatial-temporal structure of body movements is a fundamental problem for
character motion synthesis. In this work, we propose a novel neural network architecture …

In this work we present a novel, robust transition generation technique that can serve as a
new tool for 3D animators, based on adversarial recurrent neural networks. The system …

We study the problem of inferring scene affordances by presenting a method for realistically
inserting people into scenes. Given a scene image with a marked region and an image of a …

A long-standing goal in computer vision is to capture, model, and realistically synthesize
human behavior. Specifically, by learning from data, our goal is to enable virtual humans to …

Generating digital humans that move realistically has many applications and is widely
studied, but existing methods focus on the major limbs of the body, ignoring the hands and …