Spring 2023 - CMPT 764 G100

Geometric Modelling in Computer Graphics (3)

Class Number: 6936

Delivery Method: In Person


  • Course Times + Location:

    Jan 4 – Apr 11, 2023: Thu, 2:30–5:20 p.m.

  • Prerequisites:

    CMPT 361, MACM 316.



Advanced topics in geometric modelling and processing for computer graphics, such as Bezier and B-spline techniques, subdivision curves and surfaces, solid modelling, implicit representation, surface reconstruction, multi-resolution modelling, digital geometry processing (e.g., mesh smoothing, compression, and parameterization), point-based representation, and procedural modelling. Students with credit for CMPT 464 or equivalent may not take this course for further credit.


The course covers 3D modeling, as well as the basics of non-linear optimization for inverse problems. It introduces classical "Polygonal Mesh" representations, as well as the emerging "Neural Fields" (i.e. coordinate neural networks): a new representation of signals that is quickly revolutionizing computer vision/graphics. We will discuss acquisition, processing, and synthesis of 3D content, with applications to 3D machine vision, robotics, real-time 3D graphics, computational design, medical imaging, AR/VR, as well as digital art.

- The language of choice for practical exercises is Python
- This course will be cross-listed with CMPT 764

- The history of 3D scanning (and Neural Radiance Fields)
- Basics of differential geometry (Laplace Beltrami operator)
- Fairing and reconstruction (basics of Variational Calculus)
- Inverse modeling (maximum likelihood and maximum a-posteriori)
- Registration (robut least squares optimization)
- Deformation (sparse linear systems, matrix factorization)
- Compression (singular value decomposition, and transforms)
- Neural Fields (auto-decoding, neural hashing, ...)


  • One midterm 40%
  • Two homeworks 30%
  • Final Project 30%



"Polygon Mesh Processing" by Mario Botsch, Leif Kobbelt, Mark Pauly, Pierre Alliez, Bruno Levy. October 7, 2010 by A.K. Peters/CRC Press.
ISBN: 9781568814261


Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:


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