Detecting objects, estimating their pose and recovering 3D shape information is a critical problem in many vision and robotics applications. This paper addresses the above needs by...
Although mesh-based methods are efficient for simulating simple hyperelasticity, maintaining and adapting a mesh-based representation is less appealing in more complex scenarios, ...
This paper presents a novel learning framework to provide computer game agents the ability to adapt to the player as well as other game agents. Our technique generally involves a ...
When controlling an autonomous system, it is inefficient or sometimes impossible for the human operator to specify detailed commands. Instead, the field of AI autonomy has develop...
We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...