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CS580: Computer Graphics
Spring 2023
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Instructor |
Prof. Min Hyuk Kim, [Room] 3429, E3-1, [email] |
Course description
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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, )
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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
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Prerequisites |
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. |
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Week |
Date |
Lecture |
Slide |
Homework |
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1 |
02/28 |
Introduction |
KLMS |
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2 |
03/02 |
Affine transformation and frames |
KLMS |
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3 |
03/07 |
No lecture |
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4 |
03/09 |
Camera projection |
KLMS |
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5 |
03/14 |
Sampling/reconstruction/resampling |
KLMS |
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6 |
03/16 |
Raytracing (light transport) |
KLMS |
raytracing |
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7 |
03/21 |
Rendering equation |
KLMS |
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8 |
03/23 |
Reflectance for physically-based rendering (1) |
KLMS |
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9 |
03/28 |
Reflectance for physically-based rendering (2) |
KLMS |
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10 |
03/30 |
Material acquisition |
KLMS |
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11 |
04/04 |
Radiosity |
KLMS |
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12 |
04/06 |
Color |
KLMS |
radiosity |
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13 |
04/11 |
High-dynamic-range imaging(1) |
KLMS |
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14 |
04/13 |
No lecture |
KLMS |
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04/20 |
Mid-term exam (Thu: 13:00~15:45) |
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15 |
04/25 |
High-dynamic-range imaging(2) |
KLMS |
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16 |
04/27 |
Monte-Carlo integration |
KLMS |
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17 |
05/02 |
Monte-Carlo sampling |
KLMS |
path-tracing |
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18 |
05/04 |
Stochastic path tracing (1) |
KLMS |
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19 |
05/09 |
Stochastic path tracing (2) |
KLMS |
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20 |
05/11 |
Instant radiosity |
KLMS |
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21 |
05/16 |
Precomputed radiance transfer (PRT) |
KLMS |
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22 |
05/18 |
Image-based modeling (1) |
KLMS |
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23 |
05/23 |
No lecture |
KLMS |
neural rendering |
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24 |
05/25 |
Image-based modeling (2) |
KLMS |
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25 |
05/30 |
Image-based modeling (3) |
KLMS |
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26 |
06/01 |
Neural rendering (1) |
KLMS |
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27 |
06/06 |
No lecture |
KLMS |
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28 |
06/08 |
Neural rendering (2) |
KLMS |
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06/15 |
Final-term exam (Thu: 13:00~15:45) |
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Hosted by Visual Computing Laboratory, School of Computing, KAIST.
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