CSE 455: Computer Vision

Class: T/Th 10:00-11:20am, CSE2 G20

Recitation: Fri 12:30-1:20pm, JHN 102



About the course

Ever wonder how robots can navigate space and perform duties, how search engines can index billions of images and videos, how algorithms can diagnose medical images for diseases, how self-driving cars can see and drive safely or how instagram creates filters or snapchat creates masks? In this class, we will explore all of these technologies and learn to prototype them. Lying in the heart of these modern AI applications are computer vision technologies that can perceive, understand and reconstruct the complex visual world. Computer Vision is one of the fastest growing and most exciting AI disciplines in today’s academia and industry. This 10-week course is designed to open the doors for students who are interested in learning about the fundamental principles and important applications of computer vision. We will expose students to a number of real-world applications that are important to our daily lives. More importantly, we will guide students through a series of well designed projects such that they will get to implement a few interesting and cutting-edge computer vision algorithms.


Important Links

Canvas: https://canvas.uw.edu/courses/1718581/

Gradescope: https://www.gradescope.com/courses/755852 (Code: 6G2NBR)

EdStem: https://edstem.org/us/courses/57280

Course Staff + Office Hours

Instructors
Teaching Assistants
Ranjay Krishna
Jieyu Zhang
Mahtab Bigverdi
Xiaojuan Wang
Vivek Jayaram
Zihan Wang
Fatemeh Ghezloo
Minh Hoang
Ranjay Krishna
Jieyu Zhang
Mahtab Bigverdi
Xiaojuan Wang
Vivek Jayaram
Zihan Wang
Fatemeh Ghezloo
Minh Hoang
Hours: Tue 9-10am and
Hours: Tue
Hours: Mon
Hours: Fri
Hours: Thu
Hours: Mon
Hours: Wed
Hours: Tue and Thu
Thu 1:30-2:30pm
1-3pm
9-11am
1-2pm, 3-4pm
2-4pm
1-2pm, 4-5pm
9-11am
6-7pm
CSE2 304
CSE2 326
CSE 482
CSE2 275
CSE2 287
CSE2 374
CSE 4th floor breakout
Zoom link (to be posted)
ranjay@cs.
washington.edu
jieyuz2@cs.
washington.edu
mahtab@cs.
washington.edu
xiaojwan@cs.
washington.edu
vjayaram@cs.
washington.edu
avinwang@cs.
washington.edu
fghezloo@cs.
washington.edu
minh257@cs.
washington.edu

Prerequisites

Linear Algebra, Calculus and Statistics. While it is recommended to have some prior background in Machine Learning, the necessary fundamentals will be covered as part of this class.


Course format

The class format will be a combination of lectures, 5 assignments, and a final exam.