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Course Description
Course Description
In this course, our objective is to present fundamental knowledge ranging from classic computer vision methods to those inspired by deep learning. We will cover basic concepts of computer vision, explore representative problems, and discuss various solving strategies. Additionally, we aim to provide students with a historical perspective on the evolution of classical ideas in computer vision and their integration with recent advancements in deep-learning-based approaches.
General Information
General Information
Class time and location: Tuesday 13:00~15:00 / Thursday 13:00~14:00 - 310관 729호
Textbook (Reference): Deep Learning: GoodFellow
Repository: https://github.com/PiLab-CAU/ComputerVision-2501
Office Hour
Office Hour
Tuesday: 16:00~17:00, 305관 712호
Grading Policy
Grading Policy
Summary
Summary
Attendance: 10%
Midterm Exam: 35%
Final Exam: 45%
(Additional) Participation score: 10%
Opening an Issue: 3%
Add discussion comments: 1%
Note
Note
Attendance policy: Accept <=1/4 absent overall class. Offline Attendance check.
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