Lecture Notes:

Date	Lecture Notes in PPT	Lecture Notes in PDF	Readings
March 25	Introduction; ink	Introduction	None
March 27	Color and Texture; ink	Color and Texture	Joe Redmon's Color Lecture; Shapiro & Stockman Ch 6-7; HW1
April 1	Resizing; ink	Resizing	None
April 3	Filtering; ink	Filtering	Shapiro & Stockman 5.4-5.5, Szeliski 3.2, 3.3.1, Morphological operations
April 8	Edges and Lines; ink	Edges and Lines	Shapiro & Stockman 5.6-8 and 10.3.4, Szeliski 4.2.1; HW 2
April 10	Interest Operators; ink	Interest Operators	Szeliski 4.1.1, Harris Paper, SIFT paper
April 15	Describe and Match; ink	Describe and Match	Szeliski 4.1.2-4.1.3, SIFT paper
April 17	Matching and Blending; ink	Matching and Blending	Szeliski 6.1; HW3 Video
April 22	CBIR and EM; ink	CBIR and EM	S&S Ch 8; Yi's EM Classifier Paper;
April 24	Learning 1; Kadir and Fergus; ink	Learning 1; Kadir and Fergus	Related to S&S Ch 4; Kadir paper; Fergus paper
Apr 29	Face Detection and Recognition; ink	Face Detection and Recognition	Viola Jones paper; S & S Ch 14.4.4
May 1	SVMs and Neural Nets; Multi-Class; ink;	SVMs and Neural Nets; Multi-Class	Related to S & S Ch 4 and Szeliski (2nd edition) Ch 5
May 6	Object Recognition; ink	Object Recognition	Girshick Paper; Redmon's YOLO Paper; HW 4
May 8	CNN Basics; GANs	CNN Basics; GANs	PyTorch Tutorial
May 13	Self-Supervised Learning; ink	Self-Supervised Learning
May 15	Diffusion Models; ink	Diffusion Models
May 20	Motion; ink	Motion	Szeliski 8.4-8.5, S&S 9.3.4-6, Pyramid Paper; Ming Ye's paper; Motion Layers Paper
May 22	Stereo and 3D; ink	Stereo and 3D	Shapiro and Stockman Chs 12-13; HW 6