Instructor: Prof. Chenliang Xu
Instructor's Office Hours: TR 14:00-15:00, 3005 Wegmans
TA and TA's Office Hours:
Meet Time/Location: TR 12:30-13:45 in Goergen 101
Syllabus: pdf
Dicussion: This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. Find our class page here.
Fundamentals of computer vision, including image formation, elements of human vision, low-level image processing, and pattern recognition techniques. Advanced topics include modern visual features, graphical models, model-based and data-driven approaches, and contextual inference, as well as illustrative examples of successes and challenges in applications. CSC 449, a graduate-level course, requires additional readings and assignments.
Basic knowledge of probability and linear algebra; data structures, algorithms; programming experience. For assignments and projects, the most common programming language is Python.
This is a tentative schedule of the course and will be modified over the semester.
Course materials will be posted on Blackboard.
Dates | Tuesday (T) | Thursday (R) | HW Due | Project |
---|---|---|---|---|
1/17 | No Class: Before Term | Introduction | ||
1/22,24 | Linear Filtering and Image Transforms | Edges | T: 1 Out | |
1/29,31 | Corners | SIFT and Feature Matching | Sat: 1 Due (ext.) | |
2/5,7 | Neural Network and Backpropagation | CNN and Feature Visualization | Tue: 2 Out | |
2/12,14 | Fitting I | Fitting II and Alignment | ||
2/19,21 | Dense Motion Estimate | Case Study: Object Tracking | Tue: 2 Due (ext.) Tue: 3 Out |
|
2/26,28 | Segmentation I | Segmentation II | ||
3/5,7 | RNN and Image Captioning | Cancelled | ||
3/12,14 | No Class: Spring Break | No Class: Spring Break | Sat: 3 Due (ext.) | |
3/19,21 | Case Study: Image Captioning | Midterm Exam | Tue: 4 Out | |
3/26,28 | Advanced CNNs I | Advanced CNNs II | Sat: 4 Due | Train/Val Out |
4/2,4 | Object Recognition I | Object Recognition II | Tue: 5 Out | |
4/9,11 | GAN and Image Synthesizing | Visual and Sound | ||
4/16,18 | Face Recognition, Style Transfer | Video Analysis | Tue: Test Out | |
4/23,25 | Camera Models, Light and Color | Stereo Vision | Tue: Submit Due | |
4/30 | Project Presentation | No Class: Term Finished | Sat: 5 Due |
This course primarily uses Blackboard to manage information flow. The course ID is CSC249.2019SPRING.52339. It will be used for announcements, posting lecture notes and assignments, discussions and submitting work. The instructor's course website contains an outline of course schedule, which will be updated over the term, and also serves for the purpose of a syllabus.