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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

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

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

FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution

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

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Publication

Kalman Filter-based Algorithms for Estimating Depth from Image Sequences

Larry Matthies, Rick Szeliski, Takeo Kanade

International Journal of Computer Vision | August 1989, Vol 3(3): pp. 209-238

Publication

Higher-Order Unification with Dependent Function Types

Conal M. Elliott

April 1989

Publication

Incremental estimation of dense depth maps from image sequences

L. Matthies, Rick Szeliski, T. Kanade

1988 Computer Vision and Pattern Recognition | June 1988

Publication

Smooth Subdivision Surfaces Based on Triangles

Charles Loop

January 1987

January 1987

Publication

Determining grasp configurations using photometric stereo and the PRISM binocular

Katsushi Ikeuchi, H K Nishihara, Berthold K. P. Horn, P Sobalvarro, S Nagata

The International Journal of Robotics Research | March 1986, Vol 5(1): pp. 46-65

Publication

The Mechanical Manipulation of Randomly Oriented Parts

Berthold K. P. Horn, Katsushi Ikeuchi

Scientific American | July 1984, Vol 251(2): pp. 100-111

Publication

A laser rangefinder for robot control and inspection

Sarangarajan Parthasarathy, J. Birk, J. Dessimoz

Proc. of Photo-Optical Instrumentation Engineers, Robot VIsion | November 1982

Publication

Numerical shape from shading and occluding boundaries

Katsushi Ikeuchi, Berthold K. P. Horn

Artificial Intelligence | July 1981, Vol 17(1): pp. 141-184

Publication

Summer Vision Programs

October 1966

Massachusetts Institute of Technology, Project MAC Memorandum MAC-M-332, Artificial Intelligence Project Memo Number Vision 111

Video

Sketch Segmentation & Recognition

| Changhu Wang

Click to download video We study the problem of how to segment a freehand sketch at the object level. By carefully considering the basic principles of human perceptual organization, a real-time solution is presented to…