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MIT CSAIL6.819/6.869: Advances in Computer Vision |
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Spring 2022 |
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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 | Tue 02/01/2022 | Introduction. Simple Vision Systems | Phillip |
slides (keynote)
slides (pdf) admin slides lecture video notes: 2."Simple Vision System" |
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| 2 | Thu 02/03/2022 | Describing the Signal: pinhole, computational, and corner cameras. | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: 4."Imaging" |
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| Week 2 | |||||
| 3 | Tue 02/08/2022 | Geometry, Stereo, Intrinsic-Extrinsic Camera Parameters. | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: 5."Stereo" |
pset1 out
FAQ |
| TUT | Tue 02/08/2022 | Python Tutorial (3:30-5:30pm) | Instructor: Prafull, Moderator: Lucy |
Video Recording
materials (download folder, unzip, upload folder to GDrive) |
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| 4 | Thu 02/10/2022 | Signal Processing | Antonio |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: 12."Linear Image Filtering" 13."Fourier Analysis" |
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| TUT | Thu 02/10/2022 | Python Tutorial (2:30-4:30pm) | Instructor: Shuang, Moderator: Lucy |
Video Recording
materials (download folder, unzip, upload folder to GDrive) |
|
| Week 3 | |||||
| 5 | Tue 02/15/2022 | Spatial Linear Filters | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video |
pset1 due
pset2 out |
| 6 | Thu 02/17/2022 | Temporal Linear Filters | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: 14."Sampling and Aliasing" 23."Temporal Filters" |
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| Week 4 | |||||
| 7 | Tue 02/22/2022 | No Class | |||
| 8 | Thu 02/24/2022 | Multi-Scale Pyramids | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: 20. "Image Pyramids" |
pset2 due
pset3 out FAQ |
| Week 5 | |||||
| 9 | Tue 03/01/2022 | Introduction to Machine Learning | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 7: Learning from Examples "Chapter 8: The Problem of Generalization" |
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| 9 | Tue 03/01/2022 | PyTorch Tutorial (4:00-5:00pm) | Instructor: Geeticka, Moderator: Wei |
Video Recording
materials (download folder, unzip, upload folder to GDrive) |
|
| 10 | Thu 03/03/2022 | Neural Networks | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 9: Neural Nets" |
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| 10 | Thu 03/03/2022 | PyTorch Tutorial (4:00-5:00pm) | Instructor: Ching-Yao, Moderator Yingcheng |
Video Recording
materials (download folder, unzip, upload folder to GDrive) |
|
| Week 6 | |||||
| 11 | Tue 03/08/2022 | Stochastic Gradient Descent, Back Propogation | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 11: Backpropagation" |
pset3 due
pset4 out |
| 12 | Thu 03/10/2022 | Spatial NNs, CNNs, visualization of weights | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 21: Convolutional Neural Nets" |
|
| Week 7 | |||||
| 13 | Tue 03/15/2022 | Mechanisms of training and running networks | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video |
pset4 due
pset5 out |
| 14 | Thu 03/17/2022 | Temporal NNs, RNNs, LSTMs, Attention | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 24: Recurrent Neural Nets" |
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| Week 8 | |||||
| 15 | Tue 03/29/2022 | Representation Learning | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 29: Representation Learning" |
pset5 due |
| 16 | Thu 03/31/2022 | Scene Understanding | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 34: Object Recognition" |
Final project proposal due (guidlines)
pset6 out |
| Week 9 | |||||
| 17 | Tue 04/05/2022 | Vision for Embodied Agents | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video |
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| 18 | Thu 04/07/2022 | EHT and Image Priors | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video |
pset6 due |
| Week 10 | |||||
| 19 | Tue 04/12/2022 | Statistical Models for Images, Texture | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Statistical image models" |
pset7 out |
| 20 | Thu 04/14/2022 | Image Synthesis: structured prediction, generative models, GANs, autoregressive models | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 30: Generative models, Chapter 31: Generative modeling meets representation learning" |
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| Week 11 | |||||
| 21 | Tue 04/19/2022 | Probabilistic Graphical Models | Bill |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 28: Probabilstic graphical models," "Chapter 29: Inference in graphical models" |
pset7 due
pset8 out |
| 22 | Thu 04/21/2022 | Fairness / ethics in CV | Emily Denton |
slides
lecture video |
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| Week 12 | |||||
| 23 | Tue 04/26/2022 | 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) lecture video notes: "Chapter 41, 42, 43" |
pset8 due |
| 24 | Thu 04/28/2022 | Datasets, curation, biases and domain adaptation | Phillip |
slides (keynote)
slides (pptx) slides (pdf) lecture video notes: "Chapter 32: Data bias and shift, Chapter 33a: Training for robustness, Chapter 33b: Transfer learning and adaptation" |
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| Week 13 | |||||
| 25 | Tue 05/03/2022 | Invited talk | Alyosha Efros | lecture video | |
| 26 | Thu 05/05/2022 | Final Project Presentations | lecture video | ||
| Week 14 | |||||
| Tue 05/10/2022 | Final Project Presentations | Final Project Writeup due | |||