GAMES Webinar 2021 – 177期(绘制专题) | 王贝贝 (南京理工大学),Zehui Lin (Peking University)

【GAMES Webinar 2020-177期】(绘制专题)

报告嘉宾1: 王贝贝(南京理工大学)


报告题目:Path Cuts: Efficient Rendering of Pure Specular Light Transport


In scenes lit with sharp point-like light sources, light can bounce several times on specular materials before getting into our eyes, forming purely specular light paths. However, to our knowledge, rendering such multi-bounce pure specular paths has not been handled in previous work: while many light transport methods have been devised to sample various kinds of light paths, none of them are able to find multi-bounce pure specular light paths from a point light to a pinhole camera. In this paper, we present path cuts to efficiently render such light paths. We use a path space hierarchy combined with interval arithmetic bounds to prune non-contributing regions of path space, and to slice the path space into regions small enough to empirically contain at most one solution. Next, we use an automatic differentiation tool and a Newton-based solver to find an admissible specular path within a given path space region.We demonstrate results on several complex specular configurations, including RR, TT, TRT and TTTT paths.


王贝贝,女,南京理工大学,副教授,硕士生导师,中国计算机学会CAD&CG专委会委员。主要研究方向是计算机图形学渲染方向,包括了全局光照算法、参与性介质光线传递和复杂材质模型等。王贝贝分别于2009年、2014年在山东大学获得学士、博士学位,期间在巴黎高科进行两年联合培养。2015年在英国游戏公司Studio Gobo参与Disney游戏Infinity 3的研发。2015年底到2017年初,在INRIA(法国信息与自动化研究所)从事博士后研究。之后加入到南京理工大学。共发表高水平论文30余篇,其中以第一作者在ACM TOG, IEEE TVCG, CGF上发表论文十余篇。EGSR 2021, HPG 2021程序委员会委员。 ACM TOG, Siggraph Asia, EG 等期刊会议审稿人。


报告嘉宾2:Zehui Lin (Peking University)


报告题目:CPPM: Chi-squared Progressive Photon Mapping


We present a novel chi-squared progressive photon mapping algorithm (CPPM) that constructs an estimator by controlling the bandwidth to obtain superior image quality. Our estimator has parametric statistical advantages over prior nonparametric methods. First, we show that when a probability density function of the photon distribution is subject to uniform distribution, the radiance estimation is unbiased under certain assumptions. Next, the local photon distribution is evaluated via a chi-squared test to determine whether the photons follow the hypothesized distribution (uniform distribution) or not. If the statistical test deems that the photons inside the bandwidth are uniformly distributed, bandwidth reduction should be suspended. Finally, we present a pipeline with a bandwidth retention and conditional reduction scheme according to the test results. This pipeline not only accumulates sufficient photons for a reliable chi-squared test, but also guarantees that the estimate converges to the correct solution under our assumptions. We evaluate our method on various benchmarks and observe significant improvement in the running time and rendering quality in terms of mean squared error over prior progressive photon mapping methods.


The speaker graduated with a bachelor’s degree in computer science from the School of Electronics Engineering and Computer Science, Peking University, and currently studies for a master’s degree in the School of Electronics Engineering and Computer Science, Peking University with a major in software and theory in graphics. He mainly studies global light illumination algorithms for offline rendering such as photon mapping, 2020 As the first author in May 2005, he submitted “CPPM: Chi-squared Progressive Photon Mapping” to the SIGGRAPH Asia 2020 conference and was accepted and published in the Transaction on Graphics (TOG) journal. More introduction to the paper can be found on the project homepage:


徐昆,清华大学计算机系教研系列副教授,博士生导师。2009年毕业于清华大学获博士学位。研究方向为计算机图形学,主要从事真实感绘制、可视媒体内容编辑与生成等方面的研究。发表SCI论文20余篇,其中10余篇发表在ACM TOG, IEEE TVCG等重要期刊和会议上。曾获国家自然科学奖二等奖(排名第4),国家科技进步奖二等奖(排名第4),获国家优秀青年科学基金资助。个人主页:

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