Course Description

An introduction to concepts and applications in computer vision primarily dealing with geometry and 3D understanding. Topics include: cameras and projection models, low-level image processing methods such as filtering and edge detection; mid-level vision topics such as segmentation and clustering; shape reconstruction from stereo; high-level vision topics such as learned low-level visual representations; depth estimation and optical/scene flow; 6D pose estimation and object tracking. Prerequisites: linear algebra, basic probability and statistics.

Class Time and Location

Winter quarter (Jan-March, 2021).
Lecture: Monday, Wednesday 11:30am-12:50pm
Section: Friday 11:00am-12:00pm, Remote

Office Hours

Andrey Kurenkov: Tuesday 11am-1pm (remote), Thursday 3-5pm
JunYoung Gwak: Monday 10-11am (remote), Tuesday 10-11am, Wednesday 9-11am
Yinan Zhang: Wednesday 4:30-6:30pm, Friday 1 - 3pm (remote)
Krishnan Srinivasan: Monday 2-3pm, Wednesday 2-4pm, Thursday 5-6pm, Friday 5-6pm (remote)
Chen Wang: Thursday 9-11am (remote), Thursday 1-2pm, Friday 5-6pm
Jeannette Bohg: Fri 9-10am or by appointment
Silvio Savarese: Friday 2:00-3:00pm or by appointment

Grading Policy

See the Grading Page for more details on grading.

Course Discussions

Use the link to Ed found on Canvas.

Assignment Details

See the Assignment Page for more details on how to hand in your assignments.

Course Project Details

See the Project Page for more details on the course project.



Can I take this course on credit/no credit basis?
Yes. Credit will be given to those who would have otherwise earned a C- or above.
Can I audit or sit in?
In general we are very open to sitting-in guests if you are a member of the Stanford community (registered student, staff, and/or faculty). Out of courtesy, we would appreciate that you first email us or talk to the instructor to be added to the class on Canvas.
Is there a textbook for this course?
For the geometry part of the project, there are self-contained course notes that cover the material thoroughly. However, we do recommend some some textbooks for this course, and they usually can be found at Stanford Libraries. The recommended textbooks are
  • D. A. Forsyth and J. Ponce. Computer Vision: A Modern Approach (2nd Edition). Prentice Hall, 2011.
  • R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2003. link
  • Sebastian Thrun, Wolfram Burgard, Dieter Fox. Probabilistic robotics. The MIT Press, 2005. link
Can I work in groups for the Final Project?
Yes, in groups of up to three people.
I have a question about the class. What is the best way to reach the course staff?
Stanford students please use an internal class forum on Piazza so that other students may benefit from your questions and our answers. If you have a personal matter, email us at the class instructors mailing list ( .
Can I combine the Final Project with another course?
Yes, you may. There are a couple of courses concurrently offered with CS231A that are natural choices, such as CS231N (Convolutional Neural Networks, by Prof. Fei-Fei Li). Speak to the instructors if you want to combine your final project with another course.