Spatial AI Lab – Zurich: Advancements in Computer Vision and 3D Reconstruction

Spatial AI Lab – Zurich

This page provides an overview of the Spatial AI Lab at Microsoft Research in Zurich, focusing on their research in computer vision, 3D reconstruction, and related areas. The lab is led by Marc Pollefeys, a Partner Director of Science.

Research Areas:

The Spatial AI Lab's research spans several key areas within artificial intelligence and computer vision:

Computer Vision: This includes a broad range of topics such as image retrieval, 3D reconstruction, and semantic understanding of visual data.
3D Reconstruction: The lab focuses on various techniques for creating 3D models from images and sensor data, including volumetric semantic 3D reconstruction, indoor-outdoor alignment, and pixelwise view selection for multi-view stereo.
Spatial AI: This encompasses the development of AI systems that can understand and interact with the physical world, often involving techniques like Simultaneous Localization and Mapping (SLAM), augmented reality (AR), and virtual reality (VR).
Machine Learning and Deep Learning: The lab leverages these technologies to advance their research in computer vision and spatial AI, enabling more robust and accurate solutions.

Key Publications and Contributions:

The lab has a significant publication record, with many contributions to top-tier computer vision conferences and journals. Some notable publications include:

"An Overview of Recent Progress in Volumetric Semantic 3D Reconstruction" (2016): This paper provides a comprehensive review of the state-of-the-art in reconstructing 3D scenes with semantic understanding.
"A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval" (2016): This work focuses on efficient methods for matching images based on spatial relationships.
"Face reconstruction on mobile devices using a height map shape model and fast regularization" (2016): This publication explores techniques for real-time 3D face reconstruction on mobile platforms.
"Indoor-outdoor 3d reconstruction alignment" (2016): Addresses the challenge of aligning 3D reconstructions from different environments.
"Pixelwise view selection for unstructured multi-view stereo" (2016): Introduces a method for optimizing view selection in multi-view stereo reconstruction.
"Multi-Label Semantic 3D Reconstruction Using Voxel Blocks" (2016): Proposes a method for reconstructing 3D scenes with multiple semantic labels.
"A Symmetry Prior for Convex Variational 3D Reconstruction" (2016): Explores the use of symmetry priors to improve 3D reconstruction quality.
"Semantic 3d reconstruction of heads" (2016): Focuses on reconstructing detailed 3D models of human heads with semantic information.
"Minimal solvers for generalized pose and scale estimation from two rays and one point" (2016): Deals with fundamental problems in estimating camera pose and scale.
"Large-Scale Outdoor 3D Reconstruction on a Mobile Device" (2016): Demonstrates the feasibility of large-scale 3D reconstruction using mobile devices.

Leadership and Team:

Marc Pollefeys: Partner Director of Science, leading the Spatial AI Lab.
The lab also features contributions from numerous researchers, including Pablo Speciale, Ondrej Miksik, Mihai Dusmanu, and many others, as indicated by the publication list.

Lab Information:

Address: Seestrasse 356, Zurich 8038, Switzerland.
Contact: Links to social media platforms like Facebook and X (formerly Twitter) are provided for engagement.

Connect and Learn:

The page also highlights various ways to connect with Microsoft Research, including:

Programs & Events: Information on academic programs, events, and conferences.
Connect & Learn: Access to podcasts, blogs, and forums.
About: Details about the organization, careers, and labs.

Microsoft Ecosystem:

The page also includes links to various Microsoft products and services, categorized under:

All Microsoft: Global links to security, Azure, Dynamics 365, Microsoft 365, Teams, and Windows 365.
Tech & Innovation: Information on Microsoft Cloud, AI, Azure Space, Mixed Reality, HoloLens, Viva, Quantum Computing, and Sustainability.
Industries: Resources for Education, Automotive, Financial Services, Government, Healthcare, Manufacturing, Retail, and all industries.
Partners: Links for finding, becoming, and managing partnerships, as well as Azure Marketplace and AppSource.
Resources: Access to blogs, advertising, developer centers, documentation, events, licensing, Microsoft Learn, and Microsoft Research.

Search Functionality:

A search bar is available for users to find specific information within Microsoft Research.

Image:

A background image is present on the page, likely related to the lab's visual research focus.

Navigation and Filtering:

The page includes navigation links for different sections of the lab's work, such as Overview, People, Publications, News & Features, Collaborations, Events, Videos, and Projects. A filtering system allows users to refine publication results by Research Areas, People, Publication Types, and Published Date.