CS5670 Lectures, Spring 2023
Many of the following slides are modified from
the excellent class notes of similar courses offered in other schools by Prof
Yung-Yu Chuang,
Fredo Durand,
Alyosha Efros,
Bill Freeman,
James Hays,
Svetlana Lazebnik
Andrej Karpathy
Fei-Fei Li
Srinivasa Narasimhan
Silvio Savarese
Steve Seitz,
Richard Szeliski, and
Li Zhang. The
instructor is extremely thankful to the researchers for making their notes
available online. Please feel free to use and modify any of the slides, but
acknowledge the original sources where appropriate.
All dates for lectures and unreleased assignments and homeworks are provisional. All readings are from Richard Szeliski, Computer Vision: Algorithms and Applications, 2nd Edition, unless otherwise noted.
| Class
| Date
| Topic/notes
| Readings
| Assignments, etc.
|
| |
January |
| 0 |
24 |
Introduction and Overview [ppt|pdf]
 |
Szeliski (2nd Edition) 1 |
|
| 1 |
26 |
Image filtering [ppt|pdf]
 |
Szeliski 3.1 - 3.3 |
|
| 2 |
31 |
Image filtering and edge detection [ppt|pdf]
 |
Szeliski 3.1-3.3, 7.2 |
PA1 Released |
| |
February |
| 3 |
2 |
Image Resampling[ppt|pdf]
 |
Szeliski 2.3.1, 3.4-3.5 |
|
| 4 |
7 |
Feature Detection [ppt|pdf]
 |
Szeliski 7.1 |
|
| 5 |
9 |
Feature Invariance[ppt|pdf]
|
Szeliski 7.1 |
PA1 due on Friday, Feb 11 |
| 6 |
14 |
Feature Descriptors and Feature Matching [ppt|pdf]
 |
Szeliski 7.1 |
PA2 Released |
| 7 |
16 |
Image Transformations [ppt|pdf]
 |
Szeliski 3.6 |
|
| 8 |
21 |
Image Alignment [ppt|pdf]
 |
Szeliski 6.1 |
PA2 due on Wednesday, Feb 23 |
| 9 |
23 |
RANSAC [ppt|pdf]
 |
Szeliski 6.1 |
|
| |
March |
| 10 |
2 |
Cameras [ppt|pdf]
 |
Szeliski 2.1.3-2.1.6 |
Take-home midterm exam release; |
| 11 |
7 |
Panoramas [ppt|pdf]
 |
Szeliski 8 |
PA3 Released.
Take-home midterm exam due in class; |
| 12 |
9 |
Single-view Modeling [ppt|pdf]
 |
Szeliski 11.1
Mundy and Zisserman,
Geometric Invariance in Computer Vision
(read 23.1-23.5, 23.10) |
|
| 13 |
14 |
Stereo [ppt|pdf]
 |
Szeliski 12.3-12.5 |
PA3 due on Friday, Mar 17 |
| 14 |
16 |
Light & Perception [ppt|pdf]
|
Szeliski 2.2 |
|
| 15 |
21 |
Photometric Stereo [ppt|pdf]
|
Szeliski 2.2 and 13.1 |
PA4 Released |
| 16 |
23 |
Multiview Stereo [ppt|pdf]
 |
Szeliski 12.7 |
|
| 17 |
28 |
Two-view Geometry[ppt|pdf]
 |
Szeliski 11.3 and 12.1 |
|
| 18 |
30 |
Structure from Motion[ppt|pdf]
 |
Szeliski 11.4 |
PA4 due on Friday, March 31 |
| |
April |
| 19 |
11 |
Introduction to Recognition [ppt|pdf] |
Szeliski 5.1 |
|
| 20 |
13 |
Image Classification [pdf] |
Szeliski 5.1, 5.3, 6.2 |
|
| 21 |
18 |
Convolutional Neural Networks I [pdf] |
Szeliski 5.3, 5.4 |
|
| 22 |
20 |
Inverse Graphics and Neural Radiance Fields [ppt|pdf] |
Szeliski 14.6 |
PA5 Released |
| 23 |
25 |
Training Deep Networks [ppt|pdf] |
CS 231N |
|
| 24 |
27 |
Computer Vision, Ethics, and Society [ppt|pdf] |
FATE Tutorial |
|
| |
May |
| 25 |
2 |
Image Generation [ppt|pdf] |
|
|
| 26 |
5 |
Diffusion Models [ppt|pdf] and Course Review [ppt|pdf] |
|
|
| 27 |
9 |
In-class final exam |
|
|
| |
|
|
|