Overview: This course aims to introduce core concepts in computer vision. The lectures I gave focused on the topics of image structure and deep learning. Slides can be found below, together with videos for the later lectures:
- Image Structure 1
- Image Structure 2
- Image Structure 3
- Image Structure 4
- Deep Learning 4 (video digest of this material)
- Deep Learning 5 (video digest of this material)
The image structure materials are based on course material by Roberto Cipolla. This course was delivered jointly with Ignas Budvytis. It also included a wonderful guest lecture on Fourier Feature nets from Matthew Johnson.
Full course description: Engineering Tripos IIB, 4F12: Computer Vision
Note on usage/credits: A number of slides circulating in the computer vision community (including some of mine) owe a great deal to the heroic efforts of a number of individuals. These include, but are not limited to Roberto Cipolla, David Forsyth, Steve Seitz, Svetlana Lazebnik, Alyosha Efros. I’ve attempted to credit slide content where I could find the original source, but sometimes figures are so widely used that it’s difficult to be sure of the original author. If you find missing references, please let me know. Please feel free to use the slides if you find them useful - if so, please preserve references to the original authors of content where they are noted.