The One About Visual Intelligence Through Physical Intrinsics
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More About the Sharing
Jiajun Wu (Assistant Professor, Stanford University) will share on "Understanding Visual Intelligence Through Physical Intrinsics".
Much of our visual world has intrinsic, physical structure: scenes composed of objects with their own geometry, texture, material, and physical properties. But how can we infer and represent such structure from raw visual data without hampering neural network expressiveness? Jiajun will discuss recent efforts in machine visual understanding, reconstruction, and generation, contrasting two technical approaches: leveraging intrinsics as powerful inductive biases versus grounding pre-trained vision foundation models onto intrinsics. He will demonstrate how we can now build visual intelligence that infers object shape, texture, material, and physics from a single image or video, with applications in controllable, action-conditioned 4D visual world understanding, generation, and interaction. (Technical Level: 200-300)
More About the Speaker
Dr Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI's 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Google, J.P. Morgan, Samsung, Amazon, and Meta.
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