GAMES Webinar 2024 – 354期(光线传输) | 范之闽(南京大学)，郑传焜(浙江大学)
【GAMES Webinar 2024-354期】(渲染专题-光线传输)
报告嘉宾：范之闽(南京大学)
报告时间：2024年12月26号星期四晚上8:00-8:15（北京时间）
报告题目：Specular Polynomials
报告摘要：
Finding valid light paths that involve specular vertices in Monte Carlo rendering requires solving many non-linear, transcendental equations in high-dimensional space. Existing approaches heavily rely on Newton iterations in path space, which are limited to obtaining at most a single solution each time and easily diverge when initialized with improper seeds. We propose specular polynomials, a Newton iteration-free methodology for finding a complete set of admissible specular paths connecting two arbitrary endpoints in a scene. The core is a reformulation of specular constraints into polynomial systems, which makes it possible to reduce the task to a univariate root-finding problem. We first derive bivariate systems utilizing rational coordinate mapping between the coordinates of consecutive vertices. Subsequently, we adopt the hidden variable resultant method for variable elimination, converting the problem into finding zeros of the determinant of univariate matrix polynomials. This can be effectively solved through Laplacian expansion for one bounce and a bisection solver for more bounces. Our solution is generic, completely deterministic, accurate for the case of one bounce, and GPU-friendly. We develop efficient CPU and GPU implementations and apply them to challenging glints and caustic rendering. Experiments on various scenarios demonstrate the superiority of specular polynomial-based solutions compared to Newton iteration-based counterparts.
讲者简介：
Zhimin Fan is currently a second-year M.S. student at Nanjing University, under the supervision of Jie Guo. He received his bachelor’s degree from Southeast University in 2023. His research focuses on physically-based rendering, specifically on topics related to light transport simulation including specular light transport and path guiding.
报告嘉宾：郑传焜(浙江大学室)
报告时间：2024年12月26号星期四晚上8:15-8:30（北京时间）
报告题目：NeLT: Object-Oriented Neural Light Transfer
报告摘要：
This paper presents object-oriented neural light transfer (NeLT), a novel neural representation of the dynamic light transportation between an object and the environment. Our method disentangles the global illumination (GI) of a scene into individual objects’ light transportation represented via neural networks, and then composes them explicitly. It, therefore, enables flexible rendering with dynamic lighting, cameras, materials, and objects. Our rendering features various important global illumination effects, such as diffuse illumination, glossy illumination, dynamic shadowing, and indirect illumination, which completes the capability of existing neural object representation. Experiments show that NeLT does not require path tracing or shading results as input but achieves rendering quality comparable to state-of-the-art rendering frameworks, including the recent deep learning-based denoisers.
讲者简介：
郑传焜博士目前就职于浙江大学CAD&CG全国重点实验室，担任专职研究员。在此之前，他于2024年在浙江大学CAD&CG全国重点实验室获博士学位，导师为鲍虎军教授。他的主要研究方向包括神经绘制、真实感绘制和高保真材质表示。
主持人简介：
王逸群，重庆大学计算机学院副教授，本科毕业于重庆大学，博士毕业于中国科学院自动化研究所，后于阿卜杜拉国王科技大学（KAUST）担任博士后研究员。长期从事计算机图形学、神经渲染、表面重建与几何处理等领域的研究。在SIGGRAPH，NeurIPS，CVPR，TOG，T-PAMI，TVCG等CCF A 类会议与期刊上发表论文15篇。担任CCF推荐国际期刊The Visual Computer Journal (TVCJ)副编辑、中国图学学会高级会员、GAMES执行委员会委员等学术职务。先后主持了多个国家级和省部级科研项目，部分研究成果已应用于相关公司。
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观看直播的链接：https://live.bilibili.com/h5/24617282
