Date Lecture Readings Logistics
9/7 Lecture #1 (Subhransu):
Introduction and logistics

Setup Piazza, Moodle, Gradescope

Module 1: Image Formation and Representation
9/12 Lecture #2 (Subhransu):
Radiometry

HW1 out (due 9/26)

9/14 Lecture #3 (Subhransu):
Light and color

9/16 Lecture #4 (Zezhou, Ashish):
Python tutorial (Friday)

9/19 Lecture #5 (Subhransu):
Light and color; Image formation
  • Szeliski book, Chapter 2

9/21 Lecture #6 (Subhransu):
Image formation

Module 2: Basic Image Processing
9/26 Lecture #7 (Subhransu):
Modeling images

HW2 out (due 10/10)

9/28 Lecture #8 (Subhransu):
Linear filtering

Module 3: Correspondence, Alignment, Geometry
10/3 Lecture #9 (Subhransu):
Optical flow

10/5 Lecture #10 (Subhransu):
Feature detection and matching
  • Szeliski book, Chapter 7.1

10/10 No class (Indigenous Peoples Day)
10/12 Lecture #11 (Subhransu):
Image transformations and alignment
  • Szeliski book, Chapter 8.1

10/17 Lecture #12 (Subhransu):
Applications of image alignment

HW3 out (due 11/7)

Module 4: Fundamentals of Neural Networks
10/19 Lecture #13 (Subhransu):
Intro to recognition

10/24 Lecture #14 (Subhransu, remote):
Project feedback

10/26 Lecture #15 (Subhransu, remote):
Project feedback

10/31 Lecture #16 (Subhransu):
Linear models

11/2 Lecture #17 (Subhransu):
Neural networks

11/7 Lecture #18 (Subhransu):
Neural networks

HW4 out (due 11/30)

Module 5: Advanced Topics in Recognition
11/9 Lecture #19 (Subhransu):
Transfer learning

11/14 Lecture #20 (Subhransu):
Transfer learning

11/16 Lecture #21 (Subhransu):
Object detection

11/21 Lecture #22 (Subhransu):
Object detection; Image segmentation

11/23 No class (Thanksgiving break)
11/28 Lecture #23 (Subhransu):
Image generation

11/30 Lecture #24 (Subhransu):
Image generation

12/5 Lecture #25 (Subhransu):
Unsupervised learning

12/7 Lecture #26 (Subhransu):
Unsupervised learning

12/12 Lecture #27 (Subhransu):
3D shape understanding

12/13 Poster presentations (CS 150/151)