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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

A Multi-sample, Multi-tree Approach to Bag-of-words Image Representation for Image Retrieval

Zhong Wu, Qifa Ke, Jian Sun, Harry Shum

The 12th International Conference on Computer Vision (ICCV) | September 2009

Publication

Reconstructing Building Interiors from Images

Yasutaka Furukawa, Brian Curless, Steven M. Seitz, Rick Szeliski

Twelfth IEEE International Conference on Computer Vision (ICCV 2009) | September 2009

Publication

Piecewise planar stereo for image-based rendering

Sudipta Sinha, Drew Steedly, Rick Szeliski

2009 International Conference on Computer Vision | August 2009

Publication

Low-complexity Digital Filter Geometry for Spherical Coded Imaging

Guotong Feng, Shuayb Zarar, Dirk Robinson

SPIE Novel Optical Systems Design and Optimization XII | August 2009, Vol 7429

Publication

HD View: A Software Camera for the Web

Matt Uyttendaele, Howard Good, Michael Cohen

MSR-TR-2009-95 | August 2009

Publication

SkyFinder: Attribute-based Sky Image Search

Litian Tao, Lu Yuan, Jian Sun

ACM Transaction on Graphics, Siggraph | August 2009

Publication

On Centroidal Voronoi Tessellation””Energy Smoothness and Fast Computation

Yang Liu, Wenping Wang, Bruno Lévy, Feng Sun, Dong-Ming Yan, Lin Lu, Chenglei Yang

ACM Transactions on Graphics | August 2009, Vol 28

Publication

Occlusion Reasoning for Temporal Interpolation using Optical Flow

Evan Herbst, Steve Seitz, Simon Baker

MSR-TR-2009-2014 | August 2009

University of Washington Department of Computer Science and Engineering Technical Report UW-CSE-09-08-01 Available from: http://www.cs.washington.edu/research/tr/techreports.shtml

Tool

MSR Action Data Set

This is a data set used for human action-detection experiments. It consists of a number of video sequences we have recorded.

Access

Video

Bill Gates on the Feynman Lectures

July 14, 2009

Bill Gates talks about the Feynman Lectures being available on video.

0:26

Computer Vision

Highlights