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