Schedule

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
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