CS5670 Lectures, Spring 2017

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, Noah Snavely, 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.
0 Jan 26 Introduction and Overview [ppt|pdf]
Szeliski 1  
1 26 Image filtering [ppt|pdf]
Szeliski 3.1  
3 Feb 1 Image filtering 2 [ppt|pdf]
Szeliski 3.2  
4 3 Image Resampling[ppt|pdf]
Szeliski 3.4, 2.3.1  
4 3 Features Detection [ppt|pdf]
Szeliski 4.1  
5 5 Descriptors [ppt|pdf]
Szeliski 4.1 PA1 due
6 - Feature Matching [ppt|pdf]
Szeliski 4.1  
7 - Image Transformation [ppt|pdf]
Szeliski 3.6  
8 - Alignment [ppt|pdf]
Szeliski 6.1  
9 - Alignment 2 [ppt|pdf]
Szeliski 6.1  
10 - Alignment 2[ppt|pdf]
Szeliski 2.1.3-2.1.6  
11 - Panoramas [ppt|pdf]
Szeliski 9  
12 - Single View Modeling [ppt|pdf]
Szeliski 9  
13 - Single View Modeling 2[ppt|pdf]
Szeliski 9  
14 - Stereo [ppt|pdf]
Szeliski 7  
15 - Two-View Geometry [ppt|pdf]
Szeliski 7  
16 - SfM [ppt|pdf]
Szeliski 7.1-7.4  
17 - MVS [ppt|pdf]
Szeliski 11.6  
18 - Lighting [ppt|pdf]
12  
19 - Photometric Stereo [ppt|pdf]
12  
20 - Intro to Recognition 1 [ppt|pdf]
CS 231N  
21 - Intro to Recognition 2 [ppt|pdf]
CS 231N  
22 - Recognition Basics[ppt|pdf]
CS 231N  
23 - Deep Learning[ppt|pdf]
CS 231N  
24 - CNN 1[ppt|pdf]
CS 231N  
25 - CNN 2[ppt|pdf]
CS 231N  
26 - Back Propagation[ppt|pdf]
CS 231N  
27 - CNN Structure and Training[ppt|pdf]
CS 231N  


Page maintained by Noah Snavely (snavely@cs.cornell.edu)