School of Computing

Korea Advanced Institute of Science and Technology (KAIST)

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CS588: Deep Learning based Image Search (Spring 2024)

Instructor: Sung-eui Yoon




Course overview

We extract feature points between two similar images and match them, followed by overlaying them together based on the matched points in the bottom row.

Thanks to rapid advances of digital camera and various image processing tools, we can easily create new pictures, images, and videos for various purposes. This in turn results in a huge amount of images in the internet and even in personal computers. For example, flickr, an image hosting website, contains more than five billion images and flickr members update more than three thousands image every minute.

These huge image databases pose numerous technical challenges in terms of image processing, searching, storing, etc. In this class we will discuss various scalable techniques for web-scale image/video databases and novel applications that can utilize such data.

In summary, what you will get at the end of the course:

What you will do:


Lecture schedule (subject to change)

Date Topics and slides Related material(s)
  • Feb. 26 (Mon)
Overview on the course and course policy
  • Feb. 28 (Wed)
  • Mar. 4 (Mon)
  • Mar. 6 (Wed)
  • Mar. 11 (Mon)
  • Mar. 13 (Wed)
  • Mar. 18 (Mon)
  • Mar. 20 (Wed)
  • Mar. 25 (Mon)
  • Mar. 27 (Wed)
  • Apr. 1 (Mon)
  • Apr. 3 (Wed)
  • Apr. 8 (Mon)
  • Apr. 10 (Wed)
No class due to the general election
  • Apr. 15 (Mon)
Mid-term exam
  • Apr. 17 (Wed)
  • Apr. 22 (Mon)
  • Apr. 24 (Wed)
  • Apr. 29 (Mon)
  • May. 1 (Wed)
  • May. 6 (Mon)
No class due to the substitute holiday
  • May. 8 (Wed)
  • May. 13 (Mon)
  • May. 15 (Wed)
No class due to Buddha's birthday
  • May. 20 (Mon)
  • May. 22 (Wed)
  • May. 27 (Mon)
  • May. 29 (Wed)
  • Jun. 3 (Mon)
  • Jun. 5 (Wed)
  • Jun. 10 (Mon)
  • Jun. 12 (Wed)
Final exam period

Student presentations and reports

For your presentations, please use the this powerpoint template; paper presentation guideline is available.
For your final report, please use the this latex template


Additional reference materials and links

Computer vision resources (papers, videos, code, datasets, etc.):

Paper search:


Acknowledgements: The course materials are based on those of Prof. Fei-Fei Li, Stanford. Thank you so much!


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