Schedule and Syllabus

Unless otherwise specified the course lectures and meeting times are:

Monday, Wednesday 2:15-3:30
Bishop Auditorium in Lathrop Building (map)
Event TypeDateDescriptionCourse Materials
Lecture Jan 5 Intro to Computer Vision [python tutorial] [slides]
Lecture Jan 7 Image classification, data-driven approach, k-nearest neighbor [slides] [notes]
Lecture Jan 12 Linear classification: SVM/Softmax [slides] [notes] [web demo]
Lecture Jan 14 Optimization, higher-level representations, image features [slides] [notes]
A1 Due Jan 21 Assignment #1 (kNN/SVM/Softmax) Due date [assignment #1]
Lecture Jan 21 Introduction to Neural Networks, backpropagation [backprop notes]
[neural net intro notes 1/3]
Lecture Jan 26 Getting Neural Networks to work: cross-validation process, optimization, debugging [slides]
[neural net notes part 2/3]
[neural net notes part 3/3]
Lecture Jan 28 Convolutional Neural Networks: architectures, convolution / pooling layers [slides] [notes]
Proposal due Jan 30 Couse Project Proposal due [proposal description]
Lecture Feb 2 Understanding and visualizing Convolutional Neural Networks [slides]
Lecture Feb 4 What makes ConvNets tick, Transfer Learning [slides] [notes]
A2 Due Feb 6 Assignment #2 (Neural Net / ConvNet) Due date [assignment #2]
Lecture Feb 9 Squeezing out the last few percent, Training ConvNets in practice [slides]
Midterm Feb 11 In-class midterm
Milestone Feb 16 Course Project Milestone
Lecture Feb 18 Beyond Image Classification: localization, detection, segmentation.
Recurrent Networks I: Image Captioning example
A3 Due Feb 23 Assignment #3 Due date [assignment description]
Lecture Feb 23 Invited Speaker: Evan Shelhamer: Working with Caffe, an open-source ConvNet library [slides]
Lecture Feb 25 Invited Speaker: Lubomir Bourdev, Facebook AI Research
Lecture Mar 2 Invited Speaker: Jon Shlens, Google Brain [slides]
Lecture Mar 4 Working with Caffe: hands-on tutorial with Justin [slides] [code]
[coco_animals (3.9GB)]
Lecture Mar 9 Mystery talk, Tiny ImageNet student spotlights, Recurrent Networks II, Attention Models [slides]
[Tiny ImageNet leaderboard]
Poster Presentation Mar 11 2-5pm at Gates (AT&T patio)
Final Project Due Mar 15 Final course project due date (due date moved: original was March 8) [project description]