ICCV 2025 Workshop on
ICCV 2025 Workshop on
Welcome to the Multi-modal Localization and Mapping Workshop organized at ICCV 2025 in Honolulu.
Multi-modal Localization and Mapping is an essential component of computer vision, with diverse applications in fields such as autonomous robotics, augmented reality, and beyond. This workshop aims to unite researchers, practitioners, and enthusiasts to explore the latest advancements, challenges, and innovations in multi-modal localization and mapping. By leveraging information from various sensors (e.g. camera, IMU, LiDAR, radar, and language), multi-modal approaches can significantly enhance localization and mapping accuracy in complex environments.
09:00 - 09:05 Introduction
09:05 - 09:45 Keynote talk - Yannick Burkhardt
09:45 - 10:30 Keynote talk - Marc Pollefeys
10:30 - 11:00 Coffee Break
11:00 - 11:45 Keynote talk - Angela Dai
11:45 - 13:15 Lunch Break
13:15 - 14:00 Keynote talk - Eric Brachmann
14:00 - 14:45 Keynote talk - Ayoung Kim
14:45 - 15:15 Coffee Break
15:15 - 16:00 Keynote talk - Zach Teed
16:00 - 16:45 Keynote talk - Daniel Cremers
16:45 - 17:30 Panel Discussion
17:30 - 17:35 Closing Remarks
Angela Dai is an Associate Professor at the Technical University of Munich where she leads the 3D AI Lab. Angela's research focuses on understanding how real-world 3D scenes around us can be modeled and semantically understood. Previously, she received her PhD in computer science from Stanford in 2018, advised by Pat Hanrahan, and her BSE in computer science from Princeton in 2013. Her research has been recognized through an ECVA Young Researcher Award, ERC Starting Grant, Eurographics Young Researcher Award, German Pattern Recognition Award, Google Research Scholar Award, and an ACM SIGGRAPH Outstanding Doctoral Dissertation Honorable Mention.
Ayoung Kim is an Associate Professor in the Department of Mechanical Engineering at Seoul National University (SNU), leading the Robust Perception for Mobile Robotics lab. Before joining SNU, she was at the Department of Civil and Environmental Engineering of the Korea Advanced Institute of Science and Technology (KAIST) from 2014 to 2021. Her research interest is perceptual robot autonomy for navigation and spatial representation learning.
Daniel Cremers is a Professor at TUM, where he is holding the Chair of Computer Vision & Artificial Intelligence. He is also a co-founder of Artisense, a deep-tech startup developing computer vision and AI solutions for robotics and autonomous driving. Daniel has served as an area chair for ICCV, ECCV, CVPR, ACCV, IROS, etc., and as a program chair for ACCV 2014. In 2018, he was an organizer of ECCV in Munich. His publications received several awards and have been cited more than 70000 times. In 2016, Daniel received the Leibniz Award, the biggest award in German academia.
Eric Brachmann is a senior staff scientist at Niantic Spatial, working on the Visual Positioning System. He received a doctorate in 2018 by the TU Dresden (Germany), and he was a post-doctoral researcher at the Visual Learning Lab of Prof. Rother at the University Heidelberg, until 2020. He works on 3D vision topics such as object pose estimation, camera re-localization, discrete feature matching, robust estimation and structure-from-motion. He is an expert in scene coordinate regression, which is a core element in state-of-the-art learning-based localization techniques. He publishes his work at the leading computer vision conferences, is an active reviewer and area chair. He co-organized multiple tutorials, workshops and challenges on visual localization, 6D pose estimation of objects, and robust estimation.
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 scientists and engineers to develop advanced perception capabilities for HoloLens and Mixed Reality. He was elected Fellow of the IEEE in 2012. He obtained his PhD from the KU Leuven in 1999 and was a professor at UNC Chapel Hill before joining ETH Zurich. 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.
Yannick Burkhardt is a PhD student in the Smart Robotics Lab at the Technical University of Munich (TUM), supervised by Prof. Stefan Leutenegger. His research focuses on event-based vision and its applications in robot control, exploring how asynchronous visual sensing can enhance robotic perception and decision-making.
Before starting his PhD, Yannick worked at the high-tech startup Agile Robots, where he contributed to the development of the control and motion planning stack, as well as conducting research on anthropomorphic manipulation. During his time there, he gained hands-on experience deploying advanced robotics algorithms in real-world industrial settings, particularly in the context of collaborative robots.
Zachary Teed is a member of the technical staff at World Labs. He graduated with a PhD from Princeton University in 2022 where he was a member of the Princeton Vision & Learning Lab. His previous work includes "RAFT: Recurrent All-Pairs Field Transforms for Optical Flow" and "DROID-SLAM".