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CS580: Computer Graphics

Spring 2023



Prof. Min Hyuk Kim, [Room] 3429, E3-1, [email]

Course description


This course provides an introduction to the advanced level of 3D computer graphics. The goal of this course is to learn how to simulate global illumination effects to achieve photorealistic imagery. We will study the basic methods used for ray tracing and radiosity algorithms when creating computer-generated images for use in film, games and other applications. Covered topics include the physics of light, Monte Carlo methods, path-tracing, radiosity, and other hybrid algorithms in depth.

Time and place

Tuesday and Thursday 14:30—16:00, Rm. 3444 @ E-3

Teaching assistants

Inchul Kim (ex. 7864, )
Hakyeong Kim (ex. 7864, )
Dongyoung Choi (ex. 7864, )
Sanghyeon Lee (ex. 7864, )

Reference books

Philip Dutré, Kavita Bala, Philippe Bekaert (2006) Advanced Global Illumination, 2nd ed., A K Peters Ltd.
Julie Dorsey, Holly Rushmeier, Francois Sillion (2008) Digital Modeling of Material Appearance, 1st Ed., Mogan Kaufman Steven J. Gortler (2012) Foundations of 3D Computer Graphics, MIT Press


There are no official course prerequisites. However, we strongly recommend taking the introductory course, (CS380) Introduction to Computer Graphics before taking this course. In addition, we assume some programming experience in C (or C++) and a basic knowledge of linear algebra. An exposure to physics, calculus and image processing is very useful.

Tentative schedule

In this semester, we provide partial lectures using Zoom. Use the links below. Password will be announced separately to your KAIST e-mail. Note that we will check your attendance online, except the last two extended weeks.

  Week Date Lecture Slide Homework
  1 02/28 Introduction KLMS  
  2 03/02 Affine transformation and frames KLMS  
  3 03/07 No lecture  
  4 03/09 Camera projection KLMS  
  5 03/14 Sampling/reconstruction/resampling KLMS  
  6 03/16 Raytracing (light transport) KLMS raytracing
  7 03/21 Rendering equation KLMS  
  8 03/23 Reflectance for physically-based rendering (1) KLMS  
  9 03/28 Reflectance for physically-based rendering (2) KLMS  
  10 03/30 Material acquisition KLMS  
  11 04/04 Radiosity KLMS  
  12 04/06 Color KLMS radiosity
  13 04/11 High-dynamic-range imaging(1) KLMS  
  14 04/13 No lecture KLMS  
    04/20 Mid-term exam  (Thu: 13:00~15:45)    
  15 04/25 High-dynamic-range imaging(2) KLMS
  16 04/27 Monte-Carlo integration KLMS  
  17 05/02 Monte-Carlo sampling KLMS path-tracing
  18 05/04 Stochastic path tracing (1) KLMS  
  19 05/09 Stochastic path tracing (2) KLMS  
  20 05/11 Instant radiosity KLMS  
  21 05/16 Precomputed radiance transfer (PRT) KLMS  
  22 05/18 Image-based modeling (1) KLMS
  23 05/23 No lecture KLMS neural rendering
  24 05/25 Image-based modeling (2) KLMS  
  25 05/30 Image-based modeling (3) KLMS  
  26 06/01 Neural rendering (1) KLMS  
  27 06/06 No lecture KLMS  
  28 06/08 Neural rendering (2) KLMS  
    06/15 Final-term exam (Thu: 13:00~15:45)    


Class participation: 10%
Midterm/final exams: 50% (25% each)
Assignments: 40%


Textbook website
Physically Based Rendering
Lux Render
Mitsuba Renderer
Wolfram MathWorld

Hosted by Visual Computing Laboratory, School of Computing, KAIST.