Schedule and Syllabus

Lectures are held on Tuesdays and Thursdays from 3:00pm to 4:20pm @ Building 320-105 .

Recitations are held on select Fridays from 1:30pm to 2:30pm @ Shriram 104 .

Students with Documented Disabilities: Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty. Unless the student has a temporary disability, Accommodation letters are issued for the entire academic year. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone: 723-1066, URL: https://oae.stanford.edu/). For OAE letters and requests, please email the head TA Johnny Chang.



This is the syllabus for the Winter 2024 iteration of the course.

Homework releases can be found on GitHub.

Event Type Date Description Lecture Materials
Lecture 1 Tuesday
January 9
Course introduction and Logistics
[Slides] [Recording]
I. Geometric Vision
Lecture 2 Thursday
January 11
Photometric Image Formation and Color
[Slides]
[Demo Notebook] (Video on Canvas)
Recitation 1 Friday
January 12
Python/NumPy Review I
[Blank Notebook] [Filled Notebook]
Lecture 3 Tuesday
January 16
Geometric Primitives and Transformations
[Slides] [Recording]
Lecture 4 Thursday
January 18
Pinhole Camera Model
[Slides] [Recording]
Recitation 2 Friday
January 19
Linear Algebra Review
[Slides]
HW0 Friday
January 19, 11:59pm
Homework #0 due
Lecture 5 Tuesday
January 23
Calibration
[Slides] [Recording]
Lecture 6 Thursday
January 25
Multi-view Geometry
[Slides] [Recording]
Recitation 3 Friday
January 26
Pytorch Review
II. Low-Level Vision
Lecture 7 Tuesday
January 30
Filters
Slides
Demo notebook (Video on Canvas)
Lecture 8 Thursday
February 1
Edges and Lines
Slides
Demo notebook (Video on Canvas)
Lecture 9 Tuesday
February 6
Local Features and fitting
Slides
Demo notebook (Video on Canvas)
Lecture 10 Thursday
February 8
Feature detectors and descriptors
Slides
Demo notebook (Video on Canvas)
Project 1 Friday
February 9 , 11:59pm
Project 1 due
III. Visual Pattern Recognition
Lecture 11 Tuesday
February 13
Segmentation and Clustering
Slides
Lecture 12 Thursday
February 15
Clustering: K-means and Mean-shift
Slides
Lecture 13 Tuesday
February 20
Motion and Optical Flow
Slides
Demo (Video on Canvas)
Lecture 14 Thursday
February 22
ML for CV overview 1/3
Slides
Project 2 Friday
February 23, 11:59pm
Project 2 due
Lecture 15 Tuesday
February 27
ML for CV overview 2/3
Lecture 16 Thursday
February 29
ML for CV overview 3/3
IV. Advanced Topics
Lecture 17 Tuesday
March 5
CV for Robotics & Self-driving
Lecture 18 Thursday
March 7
Understanding Videos
Lecture 19
Greg Shakhnarovich
Tuesday
March 12
3D Deep Learning
Lecture 20
Sarah Tan
Thursday
March 14
CV Ethics
Demo Day Thursday
March 21
Final project / Demo day