CS5670 Lectures, Spring 2020

The lectures are now recorded! You can find them here or on Canvas; see this page for details.

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, Alexei Efros, William 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.

This schedule is tentative. All dates for lectures and unreleased assignments and homeworks are provisional.

Class Date Topic/notes Readings Assignments, etc.
  January
0 22 Introduction and Overview [ppt|pdf]
Szeliski 1  
1 27 Image filtering [ppt|pdf]
Szeliski 3.1  
2 29 Image filtering and edge detection [ppt|pdf]
Szeliski 3.2  
  February
3 3 Image Resampling[ppt|pdf]
Szeliski 3.4, 2.3.1  
4 5 Features Detection [ppt|pdf]
Szeliski 4.1  
5 10 Feature Invariance[ppt|pdf]
Szeliski 4.1 PA1 due
6 12 Feature Descriptors [ppt|pdf]
Szeliski 4.1 video link
7 17 Image Transformations [ppt|pdf]
Szeliski 3.6 video link
8 19 Image Alignment [ppt|pdf]
Szeliski 6.1 video link
9 26 RANSAC [ppt|pdf]
Szeliski 6.1 video link
  March
10 2 Cameras [ppt|pdf]
Szeliski 2.1.3-2.1.6 PA2 due; video link
11 4 Panoramas [ppt|pdf]
Szeliski 9 Take-home midterm exam release; video link
12 9 Single View Modeling [ppt|pdf]
Szeliski 9 Take-home midterm exam due; video link
13 11 Stereo [ppt|pdf]
Szeliski 7 video link
14 16 Illumination [ppt|pdf]
Szeliski 7.2 video link
15 18 Photometric Stereo [ppt|pdf]
Szeliski 7.1-7.4 video link
16 23 Multiview Stereo [ppt|pdf]
Szeliski 11.6 video link
17 25 Structure from Motion[ppt|pdf]
Szeliski 12 video link
PA3 due on Friday
  April
18 6 Image Based Rendering [ppt|pdf]   video link
19 8 Introduction to Recognition [ppt|pdf] CS 231N video link
20 13 Image Classification [ppt|pdf] CS 231N video link
21 15 Convolutional Neural Networks I [ppt|pdf] CS 231N video link PA4 due on Friday
22 20 Convolutional Neural Networks II [ppt|pdf] CS 231N video link
23 22 Training, Transfer Learning, & Generative Models [ppt|pdf] CS 231N video link
24 27 Image Manifolds & Image Synthesis (+GANs) [ppt|pdf] CS 231N video link
25 29 Deep learning and geometry [ppt|pdf] PA5 due on Friday
26 May 4 Course wrapup & review [ppt|pdf]