Topic outline

  • General

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    Welcome to the Computer Vision class!

    Computer Vision is the branch of Computer Science whose goal is to model the real world or to recognize objects from digital images. These images can be acquired using still and video cameras, infrared cameras, radars, or specialized sensors such as those used in the medical field.

    The students will be introduced to the basic techniques of the field of Computer Vision. They will learn to apply Image Processing techniques where appropriate.

    We will concentrate on the black and white and color images acquired using standard video cameras. We will introduce basic processing techniques, such as edge detection, segmentation, texture characterization, and shape recognition.

    Instructor

    Prof. Pascal Fua
    Computer Vision Laboratory (CVLAB)
    BC 310
    E-mail: pascal.fua@epfl.ch

    Course Times and Locations

    Lectures: Monday 13:15 - 15:00 CM13

    Exercises: Tuesday 10:15 - 12:00 every other week. INM 200 (A-M), INM 202 (N-Z)

    Please check the course schedule and bring your own laptops for the exercise sessions.

    Questions

    If you have any questions please post them in the discussion forum and we will answer you.

    Contact TAs

    Chen Zhao (chen.zhao@epfl.ch)

    Aoxiang Fan (aoxiang.fan@epfl.ch)

    Corentin Dumery (corentin.dumery@epfl.ch)

    Deniz Mercadier (deniz.mercadier@epfl.ch)

    Yingxuan You (yingxuan.you@epfl.ch)

    Zhantao Deng (zhantao.deng@epfl.ch)


    Graded Exercise Sessions

    We will grade two of the exercise sessions. They will count for 10% of you final grade each. There will be around two hours for you to implement some algorithms. You must join the graded exercise sessions in person, otherwise you will lose the points.

    Recorded Lectures

    The lectures will be recorded and deposited on this channel.

    Final exam

    It will be a 90min closed book exam with multiple-choice and open-ended questions. You will be allowed ONE double-sided hand-written (non-digital, non printed) A4 page of notes. It will count for 80% of your final grade. 

  • Course Schedule


    17-02-2025
    Course
    24-02-2025
    Course
    25-02-2025
    Exercise Session 1
    03-03-2025
    Course
    10-03-2025
    Course
    11-03-2025
    Exercise Session 2
    17-03-2025
    Course
    24-03-2025
    Course
    25-03-2025
    Exercise Session 3 GRADED
    31-03-2025
    Course
    07-04-2025
    Course
    08-04-2025
    		Exercise Session 4
    14-04-2025
    		Course
    28-04-2025
    Course
    29-04-2025
    Exercise Session 5
    05-05-2025
    Course
    12-05-2025
    Course
    13-05-2025
    Exercise Session 6 GRADED
    19-05-2025
    Course
    20-05-2025
    Exercise Session 7

  • Reference Text Books

    R. Szeliki, Computer Vision: Computer Vision: Algorithms and Applications, 2021.

    R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2003.


  • Introduction to the Class