1st Workshop on Scalable 3D Scene Generation and Geometric Scene Understanding

Marc Pollefeys is a Professor of Computer Science at ETH Zurich and the Director of the Microsoft Mixed Reality and AI Lab in Zurich where he works with a team of scien- tists and engineers to develop advanced perception capabilities for HoloLens and Mixed Reality. He is best known for his work in 3D computer vision, having been the first to develop a software pipeline to automatically turn photographs into 3D models, but also works on robotics, graphics and machine learning problems. Other noteworthy projects he worked on are real-time 3D scanning with mobile devices, a real-time pipeline for 3D reconstruction of cities from vehicle mounted-cameras, camera-based self-driving cars and the first fully autonomous vision-based drone. Most recently his academic research has focused on combining 3D reconstruction with semantic scene understanding.

Zan Gojcic is a Senior Research Scientist and a Research Manager at NVIDIA Zurich, where he leads a research team focused on Neural Reconstruction and Simulation. He holds a PhD from ETH Zurich and has completed a research visit at Stanford University during his doctoral studies. Zan's expertise lies at the intersection of computer vision and computer graphics, with a particular emphasis on 3D vision and neural reconstruction. His research aims to advance large-scale reconstruction and generation of data-driven simulation environments, to enable testing and training of end-to-end robotics systems.

Lingjie Liu is the Aravind K. Joshi Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania, where she leads the Penn Computer Graphics Lab. and she is also a member of the General Robotics, Automation, Sensing \& Perception (GRASP) Lab. Previously, she was a Lise Meitner Postdoctoral Research Fellow at Max Planck Institute for Informatics. She received her Ph.D. degree at the University of Hong Kong in 2019. Her research interests are at the interface of Computer Graphics, Computer Vision, and AI, with a focus on Neural Scene Representations, Neural Rendering, Human Performance Modeling and Capture, and 3D Reconstruction.

Vincent Lepetit is a professor at ENPC ParisTech, France. Before that, he was a full professor at the Institute for Computer Graphics and Vision, TU Graz, Austria and before that, a senior researcher at CVLab, EPFL, Switzerland. His research focuses on 3D scene understanding. More exactly, he aims at reducing as much as possible the guidance a system needs to learn new 3D objects and new 3D environments: How can we remove the need for training data for each new 3D problem? Currently, even self-supervised methods often require CAD models, which are not necessarily available for any type of object. This question has both theoretical implications and practical applications, as the need for training data, even synthetic, is often a deal breaker for non-academic problems. Vincent received the Koenderick “test-of-time” award at the European Conference on Computer Vision 2020 for “Brief: Binary Robust Independent Elementary Features”. He regularly serves as an area chair of the major computer vision conferences: CVPR, ICCV, ECCV, ACCV, BMVC and as an editor for PAMI and IJCV.

Jiajun Wu is an Assistant Professor of Computer Science and of Psychology at Stanford University, working on computer vision, machine learning, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from J.P. Morgan, Samsung, Amazon, and Meta.