MIT CSAIL

6.819/6.869: Advances in Computer Vision

Fall 2019

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

Lecture Date Topic Instructor Course Materials Assignments
Week 1
1 Thu 09/05/2019 Introduction. Simple Vision Systems Phillip notes
slides (keynote)
slides (pdf)
admin slides
lecture video
Week 2
2 Tue 09/10/2019 Describing the Signal: pinhole, computational, and corner cameras. Bill slides (pdf)
lecture video
3 Thu 09/12/2019 Geometry, Stereo, Intrinsic-Extrinsic Camera Parameters. Bill slides (pdf)
lecture video
pset1 out
TUT Thu 09/12/2019 Python Tutorial (4-6pm in 36-112) Julie Materials (download folder, unzip, upload folder to GDrive)
TUT Fri 09/13/2019 Python Tutorial (10am-12pm in 38-166) Nadiia Materials (download folder, unzip, upload folder to GDrive)
Week 3
4 Tue 09/17/2019 Signal Processing Antonio notes (pdf)
slides (keynote)
slides (pdf)
lecture video
5 Thu 09/19/2019 Spatial Linear Filters Antonio slides (keynote)
slides (pdf)
notes (pdf)
lecture video
pset1 due
pset2 out
Week 4
6 Tue 09/24/2019 Temporal Linear Filters Bill slides (keynote)
slides (pdf)
notes (pdf)
notes_sampling (pdf)
lecture video
7 Thu 09/26/2019 Multi-Scale Pyramids Antonio slides (keynote)
slides (pdf)
notes (pdf)
lecture video
pset2 due
pset3 out
Week 5
8 Tue 10/01/2019 Introduction to Bayesian Inference. Color Constancy and Demosaicing. Bill slides (pdf)
video
9 Thu 10/03/2019 Statistical Models for Images Bill slides (pdf)
lecture video
pset3 due
pset4 out
Week 6
10 Tue 10/08/2019 Probabilistic Graphical Models Bill slides (pdf)
chapter (pdf)
lecture video
11 Thu 10/10/2019 Introduction to Machine Learning Phillip slides (keynote)
slides (pdf)
notes (pdf)
lecture video
pset4 due
pset5 out
Week 7
12 Thu 10/17/2019 Neural Networks Phillip slides (keynote)
slides (pdf)
notes (pdf)
lecture video
pset5 due
Week 8
13 Tue 10/22/2019 Stochastic Gradient Descent, Back Propogation Antonio slides (keynote)
slides (pdf)
notes (pdf)
lecture video
14 Thu 10/24/2019 Spatial NNs, CNNs, visualization of weights Jonas Wulff slides (pdf)
slides (keynote)
video lecture
Final project proposal due
pset6 out
TUT Fri 10/25/2019 Pytorch Tutorial (4-6pm 35-225) Shawn Tutorial
Week 9
TUT Mon 10/28/2019 Pytorch Tutorial (2-4pm 35-225) Siyuan Tutorial
15 Tue 10/29/2019 Mechanisms of training and running networks Evan slides (pdf)
Video Lecture
16 Thu 10/31/2019 Invited talk: Applications in computer vision Ce Liu Video Lecture pset6 due
Miniplaces Challenge Part 1 out
Week 10
17 Tue 11/05/2019 Temporal NNs, RNNs, LSTMs, Attention Antonio Slides (keynote)
Slides (pdf)
video lecture
TUT Wed 11/06/2019 AWS Tutorial Julie Reference
Notebook
18 Thu 11/07/2019 Representation Learning Phillip Slides (keynote)
Slides (pdf)
video lecture
Miniplaces Challenge Part 1 due
Miniplaces Challenge Part 2 out
Week 11
19 Tue 11/12/2019 Scene Understanding Phillip slides (keynote)
slides (pdf)
slides (pdf)
20 Thu 11/14/2019 Vision and Language, Image Captioning, VQA Phillip slides (keynote)
slides (pdf)
video lecture
Miniplaces Challenge Part 2 due
Week 12
21 Tue 11/19/2019 Color Bill slides Bill (pdf)
slides Phillip (pdf)
slides Phillip (keynote)
video lecture
22 Thu 11/21/2019 Image Synthesis: structured prediction, generative models, GANs, autoregressive models Phillip slides (pdf)
slides (keynote)
lecture notes
video lecture
Week 13
23 Tue 11/26/2019 How to do research; How to write papers; How to give talks Phillip, Antonio, Bill slides Bill (pdf)
slides antonio (pdf)
slides Phillip (pdf)
slides Phillip (keynote)
Week 14
24 Tue 12/03/2019 Datasets, curation, biases and domain adaptation Antonio
25 Thu 12/05/2019 Vision for embodied agents Phillip slides Phillip. Dataset bias and adaptation (pdf)
slides Phillip. Dataset bias and adaptation (key)
slides Phillip. Embodied Agents (pdf)
slides Phillip. Embodied Agents (key)
notes Phillip. Embodied Agents (pdf)
Week 15
26 Tue 12/10/2019 Final Project Presentations
Wed 12/11/2019 Final Project Writeup due