Lecture Notes:

Date	Lecture Notes in PPT	Lecture Notes in PDF	Readings
January 4	Introduction; ink	Introduction	None
January 9	Color and Texture; ink	Color and Texture	Joe Redmon's Color Lecture; Shapiro & Stockman Ch 6-7; HW1
January 11	Resizing; ink	Resizing	None
Jan 16	Filtering; ink	Filtering	Shapiro & Stockman 5.4-5.5, Szeliski 3.2, 3.3.1, Morphological operations
Jan 18	Edges and Lines; ink	Edges and Lines	Shapiro & Stockman 5.6-8 and 10.3.4, Szeliski 4.2.1; HW 2
Jan 23	Interest Operators; ink	Interest Operators	Szeliski 4.1.1, Harris Paper, SIFT paper
Jan 25	Describe and Match; ink	Describe and Match	Szeliski 4.1.2-4.1.3, SIFT paper
Jan 30	Matching and Blending; ink	Matching and Blending	Szeliski 6.1; HW3
Feb 1	CBIR and EM; ink	CBIR and EM	S&S Ch 8; Yi's EM Classifier Paper;
Feb 6	Learning 1; Kadir and Fergus; ink	Learning 1; Kadir and Fergus	Related to S&S Ch 4; Kadir paper; Fergus paper
Feb 8	Face Detection and Recognition; ink	Face Detection and Recognition	Viola Jones paper; S & S Ch 14.4.4
Feb 13	SVMs and Neural Nets; Multi-Class; ink; Multi-Class revised	SVMs and Neural Nets; Multi-Class	Related to S & S Ch 4 and Szeliski (2nd edition) Ch 5; HW4
Feb 15	Object Recognition; ink	Object Recognition	Girshick Paper; Redmon's YOLO Paper
Feb 20	CNN Basics; GANs	CNN Basics; GANs	PyTorch Tutorial; HW 5
Feb 22	Self-Supervised Learning; ink	Self-Supervised Learning
Feb 27	Diffusion Models; ink	Diffusion Models
Feb 29	Motion; ink	Motion	Szeliski 8.4-8.5, S&S 9.3.4-6, Pyramid Paper; Ming Ye's paper; Motion Layers Paper
Mar 5	Stereo and 3D; ink	Stereo and 3D	Shapiro and Stockman Chs 12-13; HW 6
Mar 7	NO CLASS	Work on Projects
Mar 11 (MONDAY)	10:30-12:30 FINAL	via zoom	Link in Canvas Soon