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Computer Vision

Enabling computers and devices to understand what they see.

Microsoft at CVPR 2024: Innovations in computer vision and AI research

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Exploring how context, culture, and character matter in avatar research

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

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Published Date

Publication

GeoS: Geodesic Image Segmentation

Antonio Criminisi, Toby Sharp, Andrew Blake

2008 European Conference on Computer Vision | October 2008

Publication

Bringing Physics to the Surface

Andrew D. Wilson, Shahram Izadi, Otmar Hilliges, Armando Garcia-Mendoza, David Kirk

UIST ’08 Proceedings of the 21st annual ACM symposium on User interface software and technology | October 2008

Video

Publication

Annotating Gigapixel Images

Qing Luan, Steven Drucker, Johannes Kopf, Ying-Qing Xu, Michael Cohen

Proceedings of the 21st annual ACM symposium on User interface software and technology | October 2008

ISBN: 978-1-59593-975-3

Publication

Going Beyond the Display: A Surface Technology with an Electronically Switchable Diffuser

Shahram Izadi, Steve Hodges, Stuart Taylor, Dan Rosenfeld, Nicolas Villar, Alex Butler, Jonathan Westhues

ACM Symposium on User Interface Software and Technology (UIST ’08) | October 2008

ACM Symposium on User Interface Software and Technology (UIST '08)

Project

Publication

Semantic Saliency Driven Camera Control for Personal Remote Collaboration

Cha Zhang, Zicheng Liu, Zhengyou Zhang, Qi Zhao

IEEE Signal Processing Society 2008 International Workshop on Multimedia Signal Processing | October 2008

Project

At Microsoft Research in Cambridge we are developing new machine vision algorithms for automatic recognition and segmentation of many different object categories. We are interested in both the supervised and unsupervised scenarios.

Project

Project InnerEye – Democratizing Medical Imaging AI

InnerEye is a research project that uses state of the art machine learning technology to build innovative tools for the automatic, quantitative analysis of three-dimensional medical images.

Publication