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, Stanford Assistant Professor of Computer Science Jiajun Wu presents 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.
Wu spoke on Oct. 28, 2020 as part of HAI’s weekly seminar series. Learn more about upcoming events: https://hai.stanford.edu/events-hub
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