CS4670/5670 Lectures, Spring 2016

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.

June 6, 2016: The course is now complete. Please contact Kavita Bala for more information.

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

Class Date Topic/notes Readings Assignments, etc.
1 Jan 27 Introduction and Overview [ppt|pdf]
Szeliski 1  
2 29 Image filtering [ppt|pdf]
Szeliski 3.1  
3 Feb 1 Image filtering 2 [ppt|pdf]
Szeliski 3.2  
4 3 Fourier Analysis [ppt|pdf]
Szeliski 3.4, 2.3.1  
5 5 Pyramids [ppt|pdf]
Szeliski 3.5 PA1 out
6 8 NumPy, SciPy, PA1 [pdf]  
7 10 Image Resampling and Edge Detection [ppt|pdf]
Szeliski 3.5, 4.2  
8 12 Edge Detection [ppt|pdf]
Szeliski 4.1 PA1 due
Feb 15 Winter Break
9 17 Feature Detection [ppt|pdf]
Szeliski 4.1  
10 19 Harris Corner Detector [ppt|pdf]
Szeliski 4.1  
11 22 Valve Visitor   HW1 out
12 24 Invariance, blob detection, and MOPS [ppt|pdf]
Szeliski 4.1 PA2 out
13 26 Feature descriptors and matching [ppt|pdf]
Szeliski 6.1  
14 29 Feature matching and transforms [ppt|pdf]
Szeliski 6.1  
15 Mar 2 Image transformations [ppt|pdf]
Szeliski 3.2  
16 4 Image alignment [ppt|pdf]
Szeliski A.2, 6.1  
17 7 RANSAC and Hough Transforms [ppt|pdf]
Szeliski 6.1  
18 9 Cameras [ppt|pdf]
Szeliski 2.1.3-2.1.6  
19 11 Cameras II [ppt|pdf]
Szeliski 2.1.3-2.1.6 PA2 due
20 14 Panoramas 1 [ppt|pdf]
Szeliski 9 HW1 due
21 16 Panoramas 2 [ppt|pdf]
Szeliski 9  
22 18 Post-Prelim   PA3 out
Mar 17 Prelim: 7:30pm, Location: KND116 (Kennedy Hall, 116)
23 21 Single-view modeling I [ppt|pdf]
Szeliski 9  
24 23 Single-view modeling II [ppt|pdf]
Szeliski 9  
25 25 Two-view stereo I [ppt|pdf]
Szeliski 7.2  
Mar 28 Spring Break
Mar 30 Spring Break
Apr 1 Spring Break
26 4 Two-view stereo II [ppt|pdf]
Szeliski 7.2  
27 6 Two-view stereo III [ppt|pdf]
Szeliski 7.1-7.4  
28 8 Photometric stereo I [ppt|pdf]
Szeliski 12.1.1  
29 11 Photometric stereo II [ppt|pdf]
Szeliski 12.1.1 PA3 due
30 13 Multi-view stereo [ppt|pdf]
Szeliski 11.6  
31 15 Structure from Motion [pdf]
Szeliski 7.1-7.4 PA4 out 4/14, HW2 out
32 18 Intro to Recognition [ppt|pdf]
Szeliski 14  
33 20 Recognition Basics [pdf]
Karpathy Notes: classification  
34 22 Linear Classifiers and ConvNets 1 [pdf]
   
35 25 ConvNets 2: Optimization and Backprop [pdf]
   
36 27 ConvNets 3 [pdf]
  PA4 due 4/26, PA5 out 4/26
37 29 ConvNets 4 [pdf]
   
38 May 2 ConvNets 5 [pdf]
   
39 4 ConvNets 6 and Research [training, grokstyle]
  HW2 due
40 6 Research    
41 9 Recognition Wrapup [pdf]
   
42 11 Conclusions [pdf]
  PA5 due 5/10
May 22 Final Exam: Sunday, 2:00pm, BTN100WEST (Barton Hall 100 West-Main Floor)


Page maintained by Kavita Bala (kb@cs.cornell.edu)