This schedule is tentative and may change.
Date | Topic | Materials |
---|---|---|
January 17 | Course Introduction |
|
January 19 | Human Vision and Color | |
January 22 | Sampling and Aliasing | |
January 24 | Linear Filters | |
January 26 | Python Crash Course |
|
January 29 | Interest Points | |
January 31 | Image Features | |
February 2 | HOG and SIFT | |
February 5 | Bag of Visual Words and Feature Matching | |
February 7 | RANSAC | |
February 9 | CANCELLED |
|
February 12 | Hough Transforms | |
February 14 | K-Means Clustering | |
February 16 | Image Segmentation and Active Contours | |
February 19 | Image Segmentation via Clustering | |
February 21 | Optical Flow | |
February 23 | Tracking | |
February 26 | Kalman Filters | |
February 28 | Camera Models | |
February 30 | Supervised Learning | |
March 4 | Camera Calibration | |
March 6 | Stereo Vision | |
March 8 | CANCELLED |
|
March 18 | Neural Networks | |
March 20 | Deep Learning | |
March 22 | Convolutional Neural Networks | |
March 25 | PyTorch Tutorial |
|
March 27 | Pytorch Lightning Tutorial |
|
March 29 | CANCELLED |
|
April 1 | Optimization for Deep Learning | |
April 3 | Object Detection |
|
April 5 | Recurrent Neural Networks | |
April 8 | CANCELLED: Solar Eclipse |
|
April 10 | Transformers | |
April 12 | Transformers for Computer Vision |
|
April 15 | Instance Segmentation |
|
April 17 | Generate Adversarial Networks |
|
April 19 | Diffusion Models | |
April 22 | Pose Estimation |
|
April 24 | Project Presentations |
|
April 26 | Project Presentations |
|
April 29 | Project Presentations |
|