| Date | Topic (with linked notes / slides) | Required readings | Assignments / Deliverables | Additional readings |
|---|---|---|---|---|
| 23/08/2018 | Introduction | |||
| 28/08/2018 | Image formation-geometry [ ppt | pdf ] |
Szeliski 2.1 | ||
| 30/08/2018 | Image formation-color [ ppt | pdf ] |
Szeliski 2.2 | ||
| 4/9/18 | Basic image processing [ ppt | pdf ] |
Szeliski 3.1-3.5, 4.2-4.3 | ||
| 6/9/18 | Grouping [ ppt | pdf ] |
Contour Detection and Hierarchical Image Segmentation | Szeliski 4.2-4.3, 5.2-5.3 | |
| 11/9/18 | Guest lecture 1 | |||
| 13/09/2018 | Guest lecture 2 | |||
| 18/09/2018 | Reconstruction - I [ ppt | pdf ] |
Project proposal due | Szeliski 6 | |
| 20/09/2018 | Reconstruction - II [ ppt | pdf ] |
Space carving | Szeliski 7 | |
| 25/09/2018 | Reconstruction - III | The correspondence problem [ ppt | pdf ] |
Assignment 1 Out | Szeliski 7, 4 | |
| 27/09/2018 | The correspondence problem [ ppt | pdf ] |
SIFT | ||
| 2/10/18 | Optical flow [ ppt | pdf ] |
Szeliski 8.4 High accuracy optical flow estimation based on a theory of warping |
||
| 4/10/18 | Intro to ML [ ppt | pdf ] |
LeCun '98 (Till Section IV) | Elements of Statistical Learning, Chapter 2 | |
| 9/10/18 | ||||
| 11/10/18 | Neural networks - I [ ppt | pdf ] |
|||
| 16/10/2018 | Neural networks - II / Transfer Learning [ ppt | pdf ] |
Residual networks | Backprop for convolution Original ImageNet winner Batch normalization One of many papers |
|
| 18/10/2018 | Semantic segmentation [ ppt | pdf ] |
|||
| 23/10/2018 | Graphical models for refinement [ ppt | pdf ] |
Szeliski 3.7 Dense CRF |
||
| 25/10/2018 | Image generation [ ppt | pdf ] |
GAN | Learning what and where to draw | |
| 30/10/2018 | Object detection [ ppt | pdf ] |
R-CNN | Assignment 2 out | Fast R-CNN
Faster R-CNN SSD |
| 1/11/2018 | Instance segmentation [ ppt | pdf ] |
Instance-FCN Mask R-CNN |
||
| 6/11/18 | Pose estimation [ ppt | pdf ] |
Convolutional pose machines | Autocontext
Inference machines |
|
| 8/11/18 | Structured prediction [ pdf] |
|||
| 13/11/18 | Learning 3D | Correspondence [ ppt | pdf ] |
Deep stereo | Perspective transformer nets | |
| 15/11/2018 | Correspondence | Vision and languag [ ppt | pdf ]e |
Visual QA
Modular architectures Learning correspondence |
||
| 20/11/2018 | Embodied cognition [ ppt | pdf ] |
RL for navigation | ||
| 22/11/2018 | ||||
| 27/11/2018 | Weak, semi, self-supervised and few-shot learning" | Learning features by watching objects move
Prototypical networks |
||
| 29/11/2018 | Questions of ethics and bias | Women also snowboard | Gender shades
Paper on identifying sexuality with deep networks and response by Meg Mitchell and colleagues |
|
| 4/12/18 | Student Presentations | All assignments due | ||
| 15/12/2018 | Final report due |