GAMES Webinar 2018-53期（Siggraph 2018论文）| 朱宇峰（英属哥伦比亚大学），彭梦琪（香港大学）

【GAMES Webinar 2018-53期（Siggraph 2018论文）】
报告嘉宾1：朱宇峰，英属哥伦比亚大学
报告时间：2018年7月5日（星期四）下午2:15 – 3:00（北京时间）
主持人：陈雪锦，中国科学技术大学（个人主页：http://staff.ustc.edu.cn/~xjchen99/）
报告题目：Blended Cured Quasi-Newton for Geometry Optimization
报告摘要：
Optimizing distortion energies over a mesh, in two or three dimensions, is a common and critical problem in physical simulation and geometry processing. We present three new improvements to the state of the art: a barrier-aware line-search filter that cures blocked descent steps due to element barrier terms and so enables rapid progress; an energy proxy model that adaptively blends the Sobolev (inverse-Laplacian-processed) gradient and L-BFGS descent to gain the advantages of both, while avoiding L-BFGS’s current limitations in distortion optimization tasks; and a characteristic gradient norm providing a robust and largely mesh- and energy-independent convergence criterion that avoids wrongful termination when algorithms temporarily slow their progress. Together these improvements form the basis for Blended Cured Quasi-Newton (BCQN), a new distortion optimization algorithm. Over a wide range of problems over all scales we show that BCQN is generally the fastest and most robust method available, making some previously intractable problems practical while offering up to an order of magnitude improvement in others.
讲者简介：
Yufeng Zhu is a PhD student at the Imager lab of University of British Columbia in Vancouver, Canada. Before that, he worked as a graduate research assistant at the Graphics Lab of Institute for Creative Technology and obtained his Master degree in computer science from University of Southern California. In 2010, he obtained his Bachelor degree in Software Engineering from Shanghai Jiaotong University. His research interests include computer graphics, scientific computing and numerical optimization.
讲者个人主页：http://www.cs.ubc.ca/~mike323/

报告嘉宾2：彭梦琪，香港大学
报告时间：2018年7月5日（星期四）下午3:00 – 3:45（北京时间）
主持人：陈雪锦，中国科学技术大学（个人主页：http://staff.ustc.edu.cn/~xjchen99/）
报告题目：Autocomplete 3D Sculpting
报告摘要：
Digital sculpting is a popular means to create organic 3D models but remains a challenging and time-consuming task. In this talk, I will present my recent research work on an assisted 3D sculpting system, that helps users, especially novices, in freely creating models with reduced input labor and enhanced output quality. Our key idea is to consider how a model is authored via dynamic workflows in addition to what is shaped in static geometry. This allows our method for more accurate analysis of user intentions and more general synthesis of shape structures.
讲者简介：
Mengqi Peng is currently a PhD student at The University of Hong Kong, advised by Dr. Li-Yi Wei. Her research focuses on human computer interaction and computer graphics, particularly to develop novel features and interfaces to assist various content creations, including 2D sketching, animation, and 3D modeling.
讲者个人主页：http://mengqipeng.github.io/

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