Reinforcement Learning is an area of Machine Learning focused on how agents can be
trained to make sequential decisions, and achieve a particular goal within an arbitrary …

Physics simulation offers the possibility of truly responsive and realistic animation. Despite
wide adoption of physics simulation for the animation of passive phenomena, such as fluids …

The incredible feats of athleticism demonstrated by humans are made possible in part by a
vast repertoire of general-purpose motor skills, acquired through years of practice and …

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

A longstanding goal in character animation is to combine data-driven specification of
behavior with a system that can execute a similar behavior in a physical simulation, thus …

We present a novel method for populating 3D indoor scenes with virtual humans that can
navigate in the environment and interact with objects in a realistic manner. Existing …

Marker-less 3D human motion capture from a single colour camera has seen significant
progress. However, it is a very challenging and severely ill-posed problem. In consequence …

Training a bipedal character to play basketball and interact with objects, or a quadruped
character to move in various locomotion modes, are difficult tasks due to the fast and …

Movement is how people interact with and affect their environment. For realistic character
animation, it is necessary to synthesize such interactions between virtual characters and …

Human motion synthesis is an important problem for applications in graphics and gaming,
and even in simulation environments for robotics. Existing methods require accurate motion …