Vincent Sitzmann

Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.

A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.

A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.

This new method draws on 200-year-old geometric foundations to give artists control over the appearance of animated characters.