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Schedule

Here’s a tentative schedule that will be updated to reflect reality as the quarter progresses. Lecture materials, assignments, and other materials will also be posted here.

Lecture notes and in-class code live in the course’s public repo.

# Date Topics Projects Problems Readings (Szeliski 2nd Ed.)
1 Tue
03/11
Intro, overview
Image formation
Image transformations
P01 1, 2.2, 3.1
recreational spreadsheets (video)
2 Thu
03/13
Linear Filtering
Convolutions
P02 3.2
3 Tue
03/18
Gradients and edges
Spatial frequency
Upsampling and downsampling
Project 1 out P03 3.5, 3.7
4 Thu
03/20
Image pyramids
Project 1
Convocation Schedule
P04 3.5
5 Tue
03/25
Panorama stitching intro
Feature detection
P05 7.1
6 Thu
03/27
Geometric transformations: linear and affine
Feature description: MOPS
P06
7 Tue
04/01
Feature matching
Basic image stitching pipeline
P07 2.1, 3.6.1
8 Thu
04/03
Projective transformations
Alignment: translation, affine
P08 3.6.1, 8.1
9 Tue
04/08
Alignment - projective
RANSAC
Project 2 out P09 8.1, 8.2
10 Thu
04/10
Inverse warping
Blending
P10
Tue
04/15
NO CLASS
Thu
04/17
NO CLASS
11 Tue
04/22
Exam review
Introduce final projects
Orientation to computer vision research literature
Final project out P11
12 Thu
04/24
Midterm Exam in-class
13 Tue
04/29
Intro to ML
Live training demo
Training/Validation/Testing
14 Thu
05/01
Overfitting/Underfitting/Parsimony
Models, Layers, and Losses used in Vision
P12
15 Tue
05/06
GPU computing/PyTorch
Final Project Worktime
Project 3 out
16 Thu
05/08
Intro to 3D geometry
Pinhole camera model
Intrinsics and Extrinsics
Pose, Triangulation, Structure from Motion
2.1, 6.1.1 - 6.1.3
17 Tue
05/13
In-class work day
Project 3, Final project
18 Thu
05/15
3D Gaussian Splatting
19 Tue
05/20
Encoders, Decoders, and Latent Spaces
Transformers
20 Thu
05/22
Final project lightning talks