How a computer learns to dribble: Practice, practice, practice: Deep reinforcement learning makes basketball video games look more realistic

How a computer learns to dribble: Practice, practice, practice: Deep reinforcement learning makes basketball video games look more realistic

By using deep reinforcement learning, players in video basketball games can glean insights from motion capture data to sharpen their dribbling skills. Researchers at Carnegie Mellon University and DeepMotion Inc., a California company that develops smart avatars, have for the first time developed a physics-based, real-time method for controlling animated characters that can learn dribbling skills from experience.

Beyond deep fakes: Transforming video content into another video's style, automatically: Applications include movie production, self-driving cars, VR content

Beyond deep fakes: Transforming video content into another video's style, automatically: Applications include movie production, self-driving cars, VR content

Researchers at Carnegie Mellon University have devised a way to automatically transform the content of one video into the style of another, making it possible to transfer the facial expressions of comedian John Oliver to those of a cartoon character, or to make a daffodil bloom in much the same way a hibiscus would.