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From Graphics, to Vision, to the Omnipresence of Deep Learning: Adapting to Making the Most Impact

Published at：: 2024.05.20

Academic lectures：Lecture｜From Graphics, to Vision, to the Omnipresence of Deep Learning: Adapting to Making the Most Impact

Speaker： Ruigang Yang CTO, Inceptio ;

Time： 2024.05.20 09:00 ~ 2024.05.20 11:00

Location： Room 202, Yue-Kong Pao Library's Annex

Abstract： This talk is probably different from a typical academic talk, in which I will give a broad introduction about my immersive experience in both academic and industry world. I will start by introducing my early work on 3D reconstruction and display, aiming to bring distant people to collaborate over space as if they were in the same room. The line of research slowly moved to the more challenging and open problem of complete 3D reconstruction from incomplete and noisy input, we found that by introducing semantics can significantly improve the reconstruction quality. Then I will present works done at Baidu Research on autonomous driving, from dataset curation, AR simulation, learning based navigation scheme, to making an excavator autonomously digging trenches. Finally I will talk about the commercialization of autonomous driving on truck, its unique technical challenges and how we address them in a production setting. Looking forward, in the era of big model (with big expense), I will present a few possible directions to bridge the gap between academic research, industrial research and commercialization.

Biography ：

 
IEEE Fellow, received his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill in 2003. He has received a CAREER Award from the National Foundation of the United States. He was a tenured professor in the Department of Computer Science at the University of Kentucky, and the director of the Robotics and Autonomous Driving Laboratory at Baidu Research Institute. Dr. Yang has published more than 150 papers in top journals and conferences in the field of computer vision and graphics, including IJCV, IEEE T-PAMI, SIGGRAPH, CVPR, and ICCV, with more than 20,000 Google Scholar citations and an H-index of 74. His primary research areas are in computer vision, robotics, and AR/VR.