CS 554: Computer Vision
- Instructor: Hamdi
- Office hours: by appointment / online
- Class hours:
- Monday 13:30-15:20; Thursday 8:30-10:20.
- While every other week we will have 2+2 hours of lectures, other
weeks there will be one 2-hours lecture. Please see the schedule below
for the dates of the lectures.
- Class room:
UPDATES / NEWS:
- Earlier you were asked to submit your literature surveys by sending an
email, however, the procedure has been changed. Please submit your
survey report and presentation slides in a single zip archive via CS554
- Earlier you were asked to submit your projects by sending an email,
however, the procedure has been changed. Please submit your project
report, codes/materials, and project presentation slides in a single zip
archive via CS554 Moodle page.
follow this link to access the online exam protocol. (Accessible
only within Bilkent network. Use VPN to access from home.
- Midterm exam will be held on Monday, 19 April 2021, starting at 12:40.
- All important dates (including homework, project/project progress, and
survey submission/presentation deadlines, and midterm date) have been
- Homework details have been announced, please see the homework section
- Lectures start as of 28 January 2021.
- When you submit your reports for survey, homework, project progress,
and project, please make sure that you use the required keyword in the
subject line of the corresponding email. For the subject line keywords
please see the Important Dates section below.
Catalog Description: Basic concepts in computational
vision. Relation to human visual perception. The analysis and understanding
of image and video data. Mathematical foundations, image representation,
feature extraction, camera geometry and image alignment, stereo and 3-D
reconstruction, convolutional neural networks, face processing, object and
scene recognition, conditional and Markov random fields, tracking, action
- R. Szeliski. Computer Vision: Algorithms and Applications,
Springer Science & Business Media, 2010. [Available
- D.A. Forsyth and Jean Ponce. Computer Vision: A Modern
Approach, Prentice Hall Professional Technical Reference,
- I. Goodfellow, Y. Bengio, A. Courville. Deep Learning,
MIT Press, 2016. [Available
|Literature Survey and Presentation
||10% + 5%
Any of the following will directly result in an F grade:
- not submitting a project or homework (including report),
- not presenting a survey on the pre-scheduled date,
- being absent in the midterm,
- being absent in a project presentation.
- Basic calculus and linear algebra.
- Basic probability theory and statistics.
- Good programming skills.
Passing Grade: No predetermined grade to pass the
Makeup Policy: Medical report holders will be entitled
for the midterm make up. Makeup exam will be
Literature Survey and Presentation:
follow this link to access the homework details. Homework
details/materials are accessible only within Bilkent network. Use VPN to
access from home.
- Groups of two students will choose a topic related to computer vision,
and prepare a short survey on it.
- Surveys should be based on about 10 papers (report:
5 pages max.).
- You will make a presentation on your survey in class. The presentation
should be in parallel with your report. Duration of your presentation
may be 10 minutes at most.
- Survey topics should be confirmed first. Very similar topics to
others’ will not be allowed (priority: first come, first served).
- Your chosen survey topic and a few lines explanation (indicating group
members) should be sent to email@example.com
by 15 February 2021, 23.59 (Turkey time).
- By groups of two students.
- Projects related to your research topics are encouraged.
- Build a “real” computer vision application and test it on some data.
- You may re-use existing code, but indicate what you code you have
re-used and what code you have developed yourself.
- Three stages:
- Proposal: one-page description of the project topic and the planning
(indicating group members) for the project should be sent to firstname.lastname@example.org
by 18 February 2021 (23:59 Turkey time)
- Progress report & presentation (report: 2 pages max.)
- Final report & presentation (report: 4 pages max.)
- Examples of projects:
- Performing face verification for automatic passport control
- Recognizing the identity or expression of faces
- Recognizing gestures for communication via sign language
- Recognizing or detecting objects in images (Pascal VOC / ImageNet)
- Segmenting parts in medical images
- Performing restoration of old, deteriorated photographs
- Performing automatic morphing of images
- Performing video stabilization using object tracking
- Identifying the writer of a piece of handwriting
Template for the Reports:
All reports (including homework report) must be prepared using the IEEE double-column transactions article template
||Date / Deadline
||19 April 2021
|Literature Survey Proposal submission
[subject line: cs554_2021s_survey]
|15 February 2021, 23:59
|Literature Survey Report submission
(including the presentation)
|6 May 2021, 23.59
|Literature Survey Presentation
||6 May 2021
|Homework submission (including the report)
[subject line: cs554_2021s_hw]
|12 April 2021, 23:59
|Project Proposal submission
[subject line: cs554_2021s_proj_proposal]
|18 February 2021, 23:59
|Project Progress Presentation
||15 April 2021
|Project Progress Report submission
[subject line: cs554_2021s_proj_progress]
|15 April 2021, 23:59
|Project Final Presentation
||10 May 2021
(including the report and presentation)
|17 May 2021, 23.59
Tentative Schedule & Lecture Notes:
Lecture notes below are downloadable only within Bilkent
network. Use VPN to
access from home.
|Introduction, human vision, overview of basics
||28 January 2021 (08:30-10:20)
||Feature point extraction,
Feature point description and matching
|01 February 2021 (13:30-15:20)
04 February 2021 (08:30-10:20)
||Homography and image stitching,
|08 February 2021 (13:30-15:20)
11 February 2021 (08:30-10:20)
||Stereo vision and depth estimation
||18 February 2021 (08:30-10:20)
||Stereo vision and depth estimation, Motion,
|22 February 2021 (13:30-15:20)
25 February 2021 (08:30-10:20)
Shape, scene, and object recognition
|04 March 2021 (08:30-10:20)
||Shape, scene, and object recognition,
Conditional and Markov random fields
|08 March 2021 (13:30-15:20)
11 March 2021 (08:30-10:20)
||25 March 2021 (08:30-10:20)
||Action recognition and motion magnification
||29 March 2021 (13:30-15:20)
01 April 2021 (08:30-10:20)
||Action recognition and motion magnification,
|08 April 2021 (08:30-10:20)
Project Progress Presentations
|12 April 2021 (13:30-15:20)
15 April 2021 (09:00-10:20)
||19 April 2021 (12:40)
||26 April 2021 (13:30-15:20)
||06 May 2021 (08:30-10:20)
||10 May 2021 (13:30-15:20)