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CIS/GRASP Seminar: Jiajun Wu, MIT, “Physical Scene Understanding”

February 15, 2019 @ 11:00 am - 12:00 pm


Human intelligence is beyond pattern recognition. From a single image, we’re able to explain what we see, reconstruct them in 3D, predict what’s going to happen, and plan our actions. In this talk, I will present our recent work on physical scene understanding—reverse-engineering these capacities to make machines that are versatile, data-efficient, and have better generalization ability. The core idea is to exploit the scene’s compositional structure by integrating deep recognition networks with generative, approximate simulation engines. I’ll focus on a few topics: building an object representation for both its geometry and physics; learning compact, interpretable dynamics models for planning and control; perception and reasoning beyond vision.


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Jiajun Wu is a Ph.D. student in Electrical Engineering and Computer Science at Massachusetts Institute of Technology. He received his B.Eng. from Tsinghua University in 2014. His research interests lie in the intersection of computer vision, machine learning, robotics, and computational cognitive science. His research has been recognized through the IROS Best Paper Award on Cognitive Robotics and fellowships from Facebook, Nvidia, Samsung, Baidu, and Adobe, and his work has been covered by major media outlets including CNN, BBC, WIRED, and MIT Tech Review.


February 15, 2019
11:00 am - 12:00 pm
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