SSP Forum: Jiajun Wu on Learning to See

The
Symbolic Systems Forum
presents

Learning to See the Physical World
Jiajun Wu
Computer Science Department

Monday, March 29, 2021
2:30 pm - 3:30 pm
Join from PC, Mac, Linux, iOS or Android (requires logging in to a Zoom account): https://stanford.zoom.us/j/99713091022?pwd=b0hna3VRUkFWWHl0TUEwcTRQYktwQT09

Zoom video recording (event completed)

ABSTRACT:

Human intelligence is beyond pattern recognition. From a single image, we're able to explain what we see, reconstruct the scene in 3D, predict what's going to happen, and plan our actions accordingly. In this talk, I will present our recent work on physical scene understanding---building versatile, data-efficient, and generalizable machines that learn to see, reason about, and interact with the physical world. The core idea is to exploit the generic, causal structure behind the world, including knowledge from computer graphics, physics, and language, in the form of approximate simulation engines, and to integrate them with deep learning. Here, deep learning plays two major roles: first, it learns to invert simulation engines for efficient inference; second, it learns to augment simulation engines for constructing powerful forward models. I'll focus on a few topics to demonstrate this idea: building scene representation for both object geometry and physics; learning expressive dynamics models for planning and control; perception and reasoning beyond vision.