Program
Keynote Speakers
Prof. Markus Gross, ETH Zürich and The Walt Disney Studios
Title:
Artificial Intelligence for Making Films
Abstract:
Recent advances in machine learning and artificial intelligence have the potential to disrupt many aspects of the traditional filmmaking process both for life action and for animation productions. At Disney Research Studios (DRS) more than 50 researchers are rethinking the film production and distribution pipeline with the help of AI in order to increase production efficiency and to support the creativity of our storytellers. To fulfill its mission, DRS closely aligns its portfolio with the technology innovation needs of the 6 major film studios of the company and continuously injects novel inventions into Disney’s film production. In this talk I will take you through the Walt Disney Studios technology innovation process and show how machine learning is already being used in film production. Examples include digital humans, virtual production technologies, rendering and animation, image quality enhancement, and much more.
Speaker's Biography:
Markus Gross is the Chief Scientist of the Walt Disney Studios and a professor of Computer Science at ETH Zürich. He is one of the leading authorities in Visual Computing, Computer Animation, Digital Humans, Virtual Reality, and AI. In his role at Disney, he leads the Studio segment’s research and development unit where he and his team are pushing the forefront of technology innovation in service of the filmmaking process. Gross has published over 500 scientific papers and holds over 100 patents. His work and achievements have been recognized widely including two Academy Awards and the ACM SIGGRAPH Steven Anson Coons Award. Gross is member of multiple academies of sciences and of the Academy of Motion Pictures Arts and Sciences.
Prof. Seung-Hwan Baek, POSTECH, South Korea
Title:
Computational Illumination for High-dimensional Visual Computing
Abstract:
Traditional visual computing has primarily focused on modeling the transport of RGB light intensity in image formation, enabling perception and reconstruction tasks at a human-level understanding. In this talk, I will introduce our recent work on computational illumination-active imaging systems that exploit richer properties of light, including spectrum, polarization, and phase. These systems open up new possibilities for high-dimensional visual computing, such as 360 degree 3D imaging, full-space holography, hyperspectral 3D reconstruction, real-time polarimetric imaging, and robust robot vision in complex scenes.
Speaker's Biography:
Seung-Hwan Baek is an Associate Professor in the Department of Computer Science and Engineering at POSTECH and is jointly affiliated with the Graduate School of AI. He leads the POSTECH Computational Imaging Group and serves as co-director of the POSTECH Computer Graphics Lab. Prof. Baek received his Ph.D. in Computer Science from KAIST and was a postdoctoral researcher at Princeton University. His research lies at the intersection of computer graphics, computer vision, AI, and optics, with a focus on capturing, modeling, and interpreting high-dimensional visual data shaped by the complex interplay of light, material, and geometry. His work has broad applications in mobile imaging, robotics, autonomous systems, AR/VR displays, and scientific instrumentation. He has been recognized with several honors, including the Asiagraphics Young Researcher Award, the Frontiers of Science Award from the International Congress of Basic Science, the Outstanding Ph.D. Thesis Award in IT from the Korean Academy of Science and Technology, the SIGGRAPH Asia Doctoral Consortium Award, the Microsoft Research Asia Ph.D. Fellowship, Naver Ph.D. Fellowship, and best application paper award and best demo award at ACCV 2014.
Prof. Beibei Wang, Nanjing University, China
Title:
The Evolution of Material Representation: From Physically-Based to Neural Networks
Abstract:
The vividness and realism of the real world come from its rich and diverse geometric structures and appearances. Among these elements, the representation of appearance is essential for achieving realism. For many years, physically-based material models have been the standard in computer graphics. However, a noticeable trend has emerged in recent years: a shift from physical to neural material representations. This presentation will explore the evolution from physical to neural material modeling, review related research conducted by our team, and offer insights into future directions for material representation.
Speaker's Biography:
Beibei Wang is a professor in the School of Intelligence Science and Technology at Nanjing University. Her research interests include appearance modeling, realistic rendering, and neural rendering. She got her B.S. in 2009 and her Ph.D. in 2014, both from Shandong University. Additionally, she spent two years as a joint Ph.D. student at Telecom ParisTech from 2012 to 2014. Following her doctoral studies, Beibei worked as a postdoctoral fellow with the INRIA (Grenoble) MAVERICK team from 2015 to 2017. She also contributed to the development of Disney Infinity while working at Studio Gobo (UK) from 2014 to 2015. She has published about thirty papers in top-tier journals and conferences, including ACM TOG, SIGGRAPH (Asia), CVPR, and ICCV. She serves on the editorial boards of the Journal of Computer Graphics Techniques and Computer Graphics Forum. She served as the Program Co-Chair of EGSR 2026 and a member of the SIGGRAPH 2025 Sorting Committee.