2024-1 Computer Vision

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

Class time and location: Tuesday 3 / Thursday 3,4 - 208관(제2공학관) 414호 <AI실습실1>

Textbook: Computer Vision: Algorithms and Applications, 2nd ed. Szeliski

Repository: https://github.com/PiLab-CAU/ComputerVision-2401

Syllabus

Office Hour

Tuesday: 14:00~15:00, 305관 712호

Grading Policy

Summary

Attendance: 10%

Assignment 1: 6%

Assignment 2: 6%

Assignment 3: 8%

Midterm Exam: 30%  35%

Final Exam: 40% 45%

(Additional) Participation score:  10%

• Opening an Issue: 3%

• Add discussion comments: 1% 

Note

Attendance policy: Accept <=1/4 absent over all class. Offline Attendance check.