MIT CSAIL

6.819/6.869: Advances in Computer Vision

Spring 2021

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This schedule is preliminary and subject to change as the term evolves.

Course notes: https://groups.csail.mit.edu/vision/cvbook/

Lecture Date Topic Instructor Course Materials Assignments
Week 1
1 Wed 02/17/2021 Introduction. Simple Vision Systems Phillip slides (keynote)
slides (pdf)
admin slides

notes:
2."Simple Vision System"
Week 2
2 Mon 02/22/2021 Describing the Signal: pinhole, computational, and corner cameras. Bill slides (keynote)
slides (pptx)
slides (pdf)
bill_intro (keynote)
bill_intro (pdf)

notes:
4."Imaging"
pset1 out
FAQ
pset1 solution
3 Wed 02/24/2021 Geometry, Stereo, Intrinsic-Extrinsic Camera Parameters. Bill slides (keynote)
slides (pptx)
slides (pdf)

notes:
5."Stereo"
TUT Thu 02/25/2021 Python Tutorial (16:00-18:00 ET) Toru materials (download folder, unzip, upload folder to GDrive)
TUT Fri 02/26/2021 Python Tutorial (10:30-12:30 ET) Wei-Chiu materials (download folder, unzip, upload folder to GDrive)
Week 3
4 Mon 03/01/2021 Signal Processing Antonio slides (keynote)
slides (pdf)

notes:
12."Linear Image Filtering"
13."Fourier Analysis"
5 Wed 03/03/2021 Spatial Linear Filters Bill slides (keynote)
slides (pdf)
slides (pptx)

notes:
15. "Blur Filters"
16. "Image Derivatives"
pset1 due
pset2 out
FAQ
pset2 solution
Week 4
6 Tue 03/09/2021 Temporal Linear Filters Bill slides (keynote)
slides (pdf)
slides (pptx)

notes:
23. "Temporal Filters"
7 Wed 03/10/2021 Multi-Scale Pyramids Bill slides (keynote)
slides (pdf)
slides (pptx)

notes:
20. "Image Pyramids"
pset2 due
pset3 out
FAQ
pset3 solution
Week 5
8 Mon 03/15/2021 Introduction to Machine Learning Phillip slides (keynote)
slides (pdf)

notes:
7. "Learning from Examples"
8. "The Problem of Generalization"
9 Wed 03/17/2021 Neural Networks Phillip slides (keynote)
slides (pdf)

notes:
9. "Neural Nets"
Please also check the "Notation" chapter, since neural net notation gets confusing fast!
pset3 due
TUT Wed 03/17/2021 Pytorch Tutorial (15:00-17:00 ET) Yen-Chen Google Colab
TUT Fri 03/19/2021 Pytorch Tutorial (10:00-12:00 ET) Shawn Google Colab
Week 6
10 Wed 03/24/2021 Spatial NNs, CNNs Phillip slides (keynote)
slides (pdf)

notes:
21. "Convolutional Neural Networks"

pset4 out
FAQ
pset4 solution
Week 7
11 Mon 03/29/2021 Stochastic Gradient Descent, Back Propogation Phillip slides (keynote)
slides (pdf)

notes:
11. "Backpropagation"
12 Wed 03/31/2021 Mechanisms of training and running networks Phillip slides (keynote)
slides (pdf)
pset4 due
Miniplaces Challenge Part 1 out
FAQ
TUT Fri 04/02/2021 AWS Tutorial (19:00-21:00 ET) Steven
Week 8
13 Mon 04/05/2021 Temporal NNs, RNNs, LSTMs, Attention Phillip slides (keynote)
slides (pdf)
TUT Mon 04/05/2021 AWS Tutorial (17:00-19:00 ET) Eric
14 Wed 04/07/2021 Representation Learning Phillip slides (keynote)
slides (pdf)

notes:
33. "Transfer Learning"
Miniplaces Challenge Part 1 due
Week 9
15 Mon 04/12/2021 Scene Understanding Phillip slides (keynote)
slides (pdf)

notes:
34. "Object Recognition"
Final project proposal due
Miniplaces Challenge Part 2 out
FAQ
16 Wed 04/14/2021 Vision for Embodied Agents Phillip slides (keynote)
slides (pdf)

notes:
35. "Intelligent Agents"
Week 10
17 Wed 04/21/2021 Statistical Models for Images, Texture Bill slides (keynote)
slides (pptx)
slides (pdf)

notes:
27. "Statistical Image Models"
pset5 out
Fri 04/23/2021 Miniplaces Challenge Part 2 due
Week 11
18 Mon 04/26/2021 Image Synthesis: structured prediction, generative models, GANs, autoregressive models Phillip slides (keynote)
slides (pdf)

notes:
31. "Generative Models"
19 Wed 04/28/2021 Probabilistic Graphical Models Bill slides (keynote)
slides (pptx)
slides (pdf)

notes:
28. "Probabilistic Graphical Models"
280. "Inference in Graphical Models"
pset5 due
pset6 out
Week 12
20 Mon 05/03/2021 EHT and Image Priors Bill slides (keynote)
slides (pptx)
slides (pdf)
21 Wed 05/05/2021 Fairness / ethics in CV Olga Russakovsky (Princeton) pset6 due
Week 13
22 Mon 05/10/2021 How to do research; How to write papers; How to give talks Bill, Phillip Bill's slides (keynote)
Bill's slides (pptx)
Bill's slides (pdf)
Phillip's slides (keynote)
Phillip's slides (pdf)
23 Wed 05/12/2021 Datasets, curation, biases and domain adaptation Phillip slides (keynote)
slides (pdf)
Week 14
24 Mon 05/17/2021 Invited talk Geoff Hinton (U. Toronto)
25 Wed 05/19/2021 Final Project Presentations
Thu 05/20/2021 Final Project Writeup due