CS59300CVD: Computer Vision With Deep Learning (Spring 2026)
Generate an image of Computer Vision.
Course Information
Computer vision is a field that focuses on building machines that can see. In this course, we will cover the fundamentals of major tasks in computer vision, starting from the basics of image formation to modern computer vision methods based on deep learning. By the end of this course, students will have a solid foundation for conducting research in computer vision and the necessary technical background to understand and implement state-of-the-art vision papers.
Pre-requisites:
- CS 37300 Data Mining & Machine Learning
- MA 26500 Linear Algebra
- STAT 41600 Probability
Textbook:
- [FP] Computer Vision: A Modern Approach by David Forsyth and Jean Ponce (2nd ed.)
- [RS] Computer Vision: Algorithms and Applications by Richard Szeliski (2nd ed.)
- [DDL] Dive into deep learning by Zhang, Aston, et al.
Grading:
The final grade will be curved and no stricter than the cutoff: A+: 97-100, A: 93-96, A-: 90-92, B+: 87-89, ..., etc.The percentage is computed following (without any rounding):
- Assignments: 50% (12.5% each assignment)
- Midterm: 25%
- Final Project: 25%
FAQ:
- Lecture slides will be posted on Brightspace. Some materials are from other Professors as referenced in the slides; Do not redistribute.
- The instructor can be best reached through Ed Discussion. Please post your questions there instead of emailing TAs.
- During office hours or on Ed Discussion, please avoid posting partial homework solutions.
- Tutorial for learning Latex with Overleaf: [Link]
Instructor & TAs
Sotiris Nousias
Instructor
Email: snousias [at] purdue.edu
Office Hour: Monday 10-11AM.
Location: Zoom
Siddharth Prabakar
TA
Email: prabakar [at] purdue.edu
Office Hour: Thursdays 11-12PM.
Location: Zoom
Time & Location
- Time: Tuesday & Thursday (4:30PM - 5:45PM)
- Location: Lawson Computer Science Building (LWSN) 1106
Other Resource
Course Schedule
The following schedule is tentative and subject to change.
| Date | Event | Description | Readings |
|---|---|---|---|
| Jan 13 | Lecture 1 | Introduction + Applied DL -- Formulation
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DDL 3 |
| Jan 15 | Lecture 2 | Applied DL -- Network & Training
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DDL 2 |
| Jan 20 | Info. | Assignment 1 Released
Select from the following: |
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| Jan 20 | Lecture 3 | Image Processing - I
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RS 2 |
| Jan 22 | Lecture 4 | Image Processing - II
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| Jan 27 | Lecture 5 | Image Filtering - I
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FP 4, DDL 7 |
| Jan 29 | Lecture 6 | Image Filtering - II + CNN
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RS 3.4 |
| Feb 3 | Lecture 7 | Edge / Corner Detection - I
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FP 5.1-5.2 |
| Feb 5 | Lecture 8 | Edge / Corner Detection - II + CNN
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FP 5.3 |
| Feb 5 | Deadline | Assignment 1 Due at 11:59PM
Select from the following: |
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| Feb 6 | Info. | Assignment 2 Released
Select from the following: |
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| Feb 10 | Lecture 9 | SIFT - I
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| Feb 12 | Lecture 10 | SIFT - II
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| Feb 17 | Lecture 11 | Fitting & Alignment - I
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FP 10.2-10.4, 22.1 |
| Feb 19 | Lecture 12 | Fitting & Alignment - II
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FP 12.1 |
| Feb 20 | Deadline | Assignment 2 Due at 11:59PM
Select from the following: |
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| Feb 24 | Lecture 13 | Fitting & Alignment - III
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| Feb 26 | Lecture 14 | Cameras, Light, and Shading - I
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FP 1 |
| Mar 3 | Guest Lecture | Invited Talk - TBD
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| Mar 5 | Break | ECCV deadline
Select from the following: |
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| Mar 10 | Lecture 15 | Cameras, Light, and Shading - II
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FP 2 |
| Mar 12 | Lecture 16 | Color + Perspective Projection - I
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FP 1 |
| Mar 17 | Break | Spring Break
Select from the following: |
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| Mar 19 | Break | Spring Break
Select from the following: |
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| Mar 23 | Deadline | Project Proposal Due at 11:59PM
Select from the following: |
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| Mar 24 | Lecture 17 | Midterm Review
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| Mar 26 | Deadline | Midterm
Select from the following: |
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| Mar 27 | Info. | Assignment 3 Released
Select from the following: |
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| Mar 31 | Lecture 18 | Perspective Projection - II
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| Apr 2 | Lecture 19 | Camera Calibration & Single-View Modeling - I
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FP 1 |
| Apr 7 | Lecture 20 | Camera Calibration & Single-View Modeling - II
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| Apr 9 | Lecture 21 | Epipolar Geometry & Structure from Motion - I
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FP 7.1 |
| Apr 10 | Deadline | Assignment 3 Due at 11:59PM
Select from the following: |
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| Apr 11 | Info. | Assignment 4 Released
Select from the following: |
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| Apr 14 | Lecture 22 | Epipolar Geometry & Structure from Motion - II
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| Apr 16 | Lecture 23 | Two/Multi-View Stereo
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| Apr 21 | Lecture 24 | Light Field Modeling
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| Apr 23 | Lecture 25 | Image Classification, Segmentation, Detection - I
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| Apr 24 | Deadline | Assignment 4 Due at 11:59PM
Select from the following: |
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| Apr 28 | Lecture 26 | Language and Vision + Final Remarks
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| Apr 30 | Presentation | Project Presentations
Select from the following: |
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| May 8 | Deadline | Final Project Report Due at 11:59PM
Select from the following: |