

Mixed Reality & AI Lab – Zurich
Highlights
Introduction
“We are envisioning the future, when relevant information appears mixed in with the world, not on your desk or on your mobile device, but in context with your environment—when and where you want it—to help you solve complicated tasks.”
–Marc Pollefeys, Lab Director, Mixed Reality and AI Lab – Zurich

The Microsoft Mixed Reality & AI Lab – Zurich is focused on building the future of mixed reality using computer vision to map and understand the environment, recognize and track relevant objects, and assist users performing tasks. The lab is also exploring the synergies between mixed reality and robotics.
Marc Pollefeys, who leads this lab, is a Partner Director of Science at Microsoft and also a Professor of Computer Science at 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.
In the context of the lab Microsoft and ETH Zurich, the top technical school in continental Europe, have established a strategic partnership allowing close collaboration in multiple areas of mixed reality and AI. The lab is further collaborating with other top institutions such as EPFL and INRIA.
The lab is currently recruiting world-class, diverse expertise across computer vision, graphics, machine learning, robotics, interaction, and software engineering.
Lab Highlights

Mixed Reality Lab Launch, Zurich event
Read more about Mixed Reality Lab Launch, Zurich event
ETH Global Lecture Series: HoloLens 2 - Unpacked
Read more about ETH Global Lecture Series: HoloLens 2 - Unpacked
Holograms, spatial anchors and the future of computer vision with Dr. Marc Pollefeys
Read more about Holograms, spatial anchors and the future of computer vision with Dr. Marc Pollefeys
Swiss Joint Research Center
Read more about Swiss Joint Research CenterLearn about our research

Privacy Preserving Image Queries for Camera Localization
Read more about Privacy Preserving Image Queries for Camera Localization
Privacy Preserving Image-Based Localization
Read more about Privacy Preserving Image-Based Localization
H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions
Read more about H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions