| (Week of) Date | Topics | Assigned Readings (due this week) | Assignments (posted on Canvas) |
|---|---|---|---|
| Aug 30 | Course Introduction and Basic Webpage Design | ||
| Sep 6 | Object Recognition and Cascading Stylesheets |
Guidelines to Reading Research Papers:
How to Read a Computer Science Research Paper,
How to Read a CS Research Paper,
How to Read an Engineering Research Paper
Object Recognition Papers: ImageNet, Fine-Grained Cars |
Reading Assignment 1 Due Sep. 5 |
| Sep 13 | Crowdsourcing and Amazon Mechanical Turk GUI (Lecture by Matthew Lease) |
Choose 2 Papers:
A Survey of General-Purpose Crowdsourcing Techniques,
Beyond Mechanical Turk: An Analysis of Paid Crowd Work Platforms,
Half Workday as a Turker
Choose 1 Paper: Demographics of Mechanical Turk, Who are the Crowdworkers? Shifting Demographics in Mechanical Turk Choose 1 Paper: Being A Turker, Turkopticon: Interrupting Worker Invisibility in Amazon Mechanical Turk, Web Workers, Unite! Addressing Challenges of Online Laborers |
Reading Assignment 2 and Lab 1 Due Sep. 12 |
| Sep 20 | Scene Classification and Javascript |
Survey Papers:
Section 1 and Section 2.1.1 of Crowdsourcing in Computer Vision,
Scene Understanding Datasets: Chapter 2
Choose 2 Papers: SUN, Places2, LSUN |
Reading Assignment 3 Due Sep. 19 and Lab 2 Due Sep. 26 |
| Sep 27 | Attribute Labeling and Amazon Mechanical Turk Command Line Tools |
Survey Paper:
Section 2.1.5 of Crowdsourcing in Computer Vision
Required Paper: a-Pascal & a-Yahoo Choose 1 Paper: Attribute Learning in Large-Scale Datasets, SUN Attribute Database Choose 1 Paper: UT Zappos50K, Caltech-UCSD Birds-200-2011 |
Reading Assignment 4 and Lab 2 Due Sep. 26 |
| Oct 4 | Object Detection and Amazon Mechanical Turk Command Line Tools | ILSVRC, Crowdsourcing Annotations for Visual Object Detection | Reading Assignment 5 Due Oct. 3 and Lab 3 Due Oct. 10 |
| Oct 11 | Segmentation and Javascript | Section 2.1.3 of Crowdsourcing in Computer Vision, LabelMe, Utility Data Annotation with Mechanical Turk, MSCOCO | Reading Assignment 6 and Lab 3 Due Oct. 10 |
| Oct 18 | Video Annotation: Object Tracking, Event Recognition | Section 2.2.2 of Crowdsourcing in Computer Vision, VATIC, ActivityNet, YouTube-8M | Course Project Pre-Proposal Due Oct. 17, Reading Assignment 7 Due Oct. 17, and Lab 4 Due Oct. 24 |
| Oct 25 | Machine Learning, Weka, and Latex | Machine learning: Trends, perspectives, and prospects, Clickstream Analysis, Instrumenting the Crowd | Reading Assignment 8 and Lab 4 Due Oct. 24, Project Proposal Due Oct. 31 |
| Nov 1 | Visual Captions, Visual Descriptions, Coding to Create AMT Input, Coding to Parse AMT Results, and Latex | Optional: Chapter 3 of Survey, Microsoft COCO Captions, MSR-VTT | Project Outline Due Nov. 14 |
| Nov 8 | Visual Question Answering and Dialog | Optional: Visual Question Answering: A Survey of Methods and Datasets, VQA: Visual Question Answering, VQA Dialog | Project Outline Due Nov. 14 |
| Nov 15 | 3D Vision, Alternative Sensors, and Subjective Problems | Optional: Beyond PASCAL: A Benchmark for 3D Object Detection in the Wild, Crowdsourcing for Reference Correspondence Generation in Endoscopic Images, Crowdsourcing for Bioinformatics, Section 2.3.2 of Crowdsourcing in Computer Vision | Project presentation on Dec. 6 and Final project submission due Dec. 12 |
| Nov 22 | No Class (Thanksgiving Break) | ||
| Nov 29 | Course Review, Synthetic Data, Active Learning, and Hybrid Human-Machine Partnerships | Project presentation on Dec. 6 and Final project submission due Dec. 12 | |
| Dec 6 | Project Presentations | Final project submission due Dec. 12 |