内容

学术讲座: Computer Graphics in the Age of AI and Big Data

阅读数:206    发布:2018-04-08 11:23    更新:2018-04-08 11:24    

Title: Computer Graphics in the Age of AI and Big Data

Time10:30 AM, 13APR, 2018

Location计算机与软件学院624

Abstract:

Computer graphics is traditionally defined as a field which covers all aspects of computer-assisted image synthesis. An introductory class to graphics mainly teaches how to turn an explicit model description including geometric and photometric attributes into one or more images. Under this classical and arguably narrow definition, computer graphics corresponds to a ``forward'' (synthesis) problem, which is in contrast to computer vision, which traditionally battles with the inverse (analysis) problem.In this talk, I would offer my view of what the NEW computer graphics is, especially in the current age of machine learning and data-driven computing. I will first remind ourselves several well-known data challenges that are unique to graphics problems. Then, by altering the above classical definition of computer graphics, perhaps only slightly, I show that to do the synthesis right, one has to first solve various inverse problems. In this sense, graphics and vision are converging, with data and learning playing key roles in both fields. A recurring challenge however is a general lack of “Big 3D Data”, which graphics research is expected to address. Finally, I want to explore a new perspective for the synthesis problem to mimic a higher-level human capability than pattern recognition and understanding.

Bio

Hao (Richard) Zhang is a full professor in the School of Computing Science at Simon Fraser University (SFU), Canada, where he directs the graphics (GrUVi) lab. He obtained his Ph.D. from the Dynamic Graphics Project (DGP), University of Toronto, and M.Math. and B.Math degrees from the University of Waterloo, all in computer science. Richard's research is in computer graphics with special interests in geometric modeling, analysis and synthesis of 3D contents (e.g., shapes and indoor scenes), machine learning (e.g., generative models for 3D shapes), as well as computational design, fabrication, and creativity. He has published more than 100 papers on these topics. He is an editor-in-chief of Computer Graphics Forum and an associate editor of several other journals. He has served on the program committees of all major computer graphics conferences including SIGGRAPH (+Asia), Eurographics, Symposium on Geometry Processing (SGP), among others, and is SIGGRAPH Asia 2014 course chair and a paper co-chair for SGP 2013, Graphics Interface 2015, and CGI 2018. He received an NSERC DAS (Discovery Accelerator Supplement) Award in 2014, Best Paper Awards from SGP 2008 and CAD/Graphics 2017, a Faculty of Applied Sciences Research Excellence Award at SFU in 2014, a National Science Foundation of China (NSFC) Overseas, Hongkong, and Macau Scholar Collaborative Research Award in 2015, and is an IEEE Senior Member. For his university service, he received the SFU Dean of Graduate Studies Awards for Excellence in Leadership in 2016. He has been a visiting professor at Stanford University, Shandong University, and Shenzhen University.


深圳大学计算机与软件学院 2009-2016