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Master of Science in

Computer Vision

Overview

This scientific field studies how computers can be used to automatically understand and interpret visual imagery. It aims to mimic the astounding capabilities of human visual cortex using machine vision algorithms. It studies how an image is created, the geometry of the 3D world and high-level tasks such as object recognition, object detection, and tracking, image segmentation and action recognition. Computer vision has important applications in augmented/virtual reality, autonomous cars, service robots, biometrics and forensics, remote sensing, and security and surveillance

  • icon Full time Mode
  • icon 36 Credits
  • icon On Campus Location

The Computer Vision (CV) Department is comprised of expert faculty and researchers that have been leading their field for decades. Though MBZUAI is new, it has amassed a truly talented team of faculty, researchers, and world-class students that mark MBZUAI as a rising star in CV innovation and research.

Ian Reid

Department Chair of Computer Vision, and Professor of Computer Vision

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Meet the Faculty

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Fahad Khan

Deputy Department Chair of Computer Vision, and Professor of Computer Vision

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Hao Li

Associate Professor of Computer Vision, and Director of MBZUAI Metaverse Center

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Salman Khan

Associate Professor of Computer Vision

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Karthik Nandakumar

Associate Professor of Computer Vision

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Mohammad Yaqub

Associate Professor of Computer Vision

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Rao Muhammad Anwer

Associate Professor of Computer Vision

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Hisham Cholakkal

Associate Professor of Computer Vision

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Muhammad Haris Khan

Associate Professor of Computer Vision

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Shahrukh Hashmi

Adjunct Professor of Computer Vision

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Min Xu

Affiliated Assistant Professor of Machine Learning

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Xiaodan Liang

Visiting Associate Professor of Computer Vision

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Hosni Ghedira

Professor of Practice of Computer Vision

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Ian Reid

Department Chair of Computer Vision, and Professor of Computer Vision

BIO
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Ivan Laptev

Professor of Computer Vision

BIO
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Xiaojun Chang

Visiting Professor of Computer Vision

BIO

A typical study plan is as follows:


SEMESTER 1

AI701 Foundations of Artificial Intelligence
MTH701 Mathematical Foundations of Artificial Intelligence
CV701 Human and Computer Vision

SEMESTER 2

CV702 Geometry for Computer Vision OR
CV703 Visual Object Recognition and Detection
+ 2 elective from list

SUMMER

INT799 Internship (up to six weeks)

SEMESTER 3

CV799 Master’s Research Thesis
RES799 Research Training

SEMESTER 4

CV799 Master’s Research Thesis

Disclaimer: Subject to change.


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