Course Info

Textbook

[1] Richard Szeliski, Computer Vision: Algorithms and Applications, 2021. Download

References

[1] Trevor Darrell's CS 280 Computer Vision class at Berkeley.
[2] Antonio Torralba's 6.869 Advances in Computer Vision class at MIT.
[3] Michael Black's CS 143Introduction to Computer Vision class at Brown.
[4] Kristen Grauman's CS 378 Computer Vision class at UT Austin.
[5] Alyosha Efros' 15-463 Computational Photography and 16-721 Learning-Based Methods in Vision classes at Carnegie Mellon.

GRADING

Homework(3 times) : 20%
Term Project : 30%
Midterm Exam : 20%
Final Exam : 30%
Absent : -3 total score each time

Announcement

  • 請負責報告的同學提前一到兩天把PPT寄給助教。

    • 點名表: Link

    • 視訊連結: Link

    • Term Project
        投影片: Link
        Proposal: 1 page




    Class Materials

    Course Links

  • Youtube



  • Handouts (2021 ~ ) (PPT Format)

  • Chapter 2: Image Formation | 2021 | 2022 | 2023 | 2024
  • Chapter 3: Image Processing | 2021 | 2022 | 2023 | 2024
  • Chapter 4: Model Fitting and Optimization | 2021 | 2022 | 2023 | 2024
  • Chapter 5: Deep Learning | 2021 | 2022 | 2023 | 2024
  • Chapter 6: Recognition | 2021 | 2022 | 2023 | 2024
  • Chapter 7: Feature Detection and Matching | 2021 | 2022 | 2023 | 2024
  • Chapter 8: Image Alignment and Stiching | 2021 | 2022 | 2023 | 2024
  • Chapter 9: Motion Estimation | 2021 | 2022 | 2023 | 2024
  • Chapter 10: Computational Photography | 2021 | 2022 | 2023 | 2024
  • Chapter 11: Structure from Motion and SLAM | 2021 | 2022 | 2023
  • Chapter 12: Depth Estimation | 2021 | 2022 | 2023
  • Chapter 13: 3D Reconstruction | 2021 | 2022 | 2023
  • Chapter 14: Image-Based Rendering | 2021 | 2022

  • Reasearch

  • 2/27   Super-Resolution
  • 3/05   Detecting Violation of Helmet Rule
  • 3/12   TIOLIDA
  • 3/19   AE and ToneMapping
  • 3/26   Hand gesture recognition
  • 3/26   SegVol
  • 4/02   FCN_ECG_REMOVAL
  • 4/16   3D MMWave for Gesture Recognition
  • 4/23   3D Face Model for Surgical Simulation and Visualization
  • Homework Regulations

  • Homeworks are to be turned in ON TIME by FTP FileZilla Client ( IP: 140.112.31.83, account: 2024cv2, password: 2024cv2, port: 12000) Late homeworks will be subjected to grade penalties! Please compress the homework files to a zip file. The filename format is Rxxxxxxxx_HWx_verx.zip (e.g. R07922666_HW1_ver1.zip).

  • Late homeworks will be subjected to grade penalties (20% off) .

  • Submissions more than three days late will not be graded.

  • Only electronic submissions are allowed! The homework should include two parts, the report and source code. Report formats are restricted to Adobe PDF format. Failure to fulfill the file formats when submitting your homework will result with no grades. Also, please take note of the fields for submission.

  • Your homework report should include the following contents: a brief discription of your homework, the algorithm you used, your parameters (if any), your principal code fragment, and the resulting images (please paste the images in your report file).

  • Do not copy homeworks from others. Copying is cheating, and cheating is shameful. You and the person who let you copy his/her homework will both get a 0. In addition, you could be subjected to an on site demostration for the following assignments.

  • Any programming language are allowed to used for homework. Do not use any library except basic I/O function (e.g. read file, write file, show image).

  • Homework 1

    Due Date : 03/05

    Homework 2

    Due Date : 03/12

    Homework 3

    Due Date : 04/30

    授課教授: 傅楸善教授

    email: fuh@csie.ntu.edu.tw
    web: http://www.csie.ntu.edu.tw/~fuh
    Tel: (02)23625336 轉 327

    課程資訊

    上課時間: 週二下午 789 節
    (2:20PM ~ 5:20PM)
    上課地點: 德田館 R105

    助教: 李詠億

    email: charlie8803290@gmail.com
    TA hour請寄信約時間

    Reference Materials