Computing Science Course Outlines

Course Outline - CMPT 762 - Computer Vision

Information

Subject

Catalog Number

Section

Semester

Title

Instructor(s)

Campus

CMPT

762

G100

2022 Spring (1221)

Computer Vision

Yasutaka Furukawa   

Burnaby Mountain Campus

Calendar Objective/Description

Computer Vision

Instructor's Objectives

Computer vision is the process of automatically extracting information from images and video. This course covers 1) image classification, object detection, and image segmentation techniques that are based on mostly deep neural networks and to some extent classical techniques; and 2) 3D computer vision techniques, including camera models, calibration, and 3D reconstruction. We will also cover other state-of-the-art deep neural architectures for computer vision applications, such as metric learning, generative adversarial networks, and recurrent neural networks.

Prerequisites

see go.sfu.ca

Grading

The grading will be based on 5 coding assignments.

Recommended Books

  • Computer Vision: Algorithms and Applications, Richard Szeliski, http://szeliski.org/Book/

Academic Honesty Statement

Academic honesty plays a key role in our efforts to maintain a high standard of academic excellence and integrity. Students are advised that ALL acts of intellectual dishonesty will be handled in accordance with the SFU Academic Honesty and Student Conduct Policies ( http://www.sfu.ca/policies/gazette/student.html ).

Data Last Updated: