Name
Abstract | ||
|---|---|---|
Machine learning techniques just recently enabled dramatic improvements in both realtime and offline rendering. In this course, we introduce the basic principles of machine learning and review their relations to rendering. Besides fundamental facts like the mathematical identity of reinforcement learning and the rendering equation, we cover efficient and surprisingly elegant solutions to light transport simulation, participating media, noise removal, and anti-aliasing.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3214834.3214841 | SIGGRAPH Courses |
Field | DocType | ISBN |
Computer graphics (images),Computer science,Integral equation,Artificial intelligence,Artificial neural network,Noise removal,Reinforcement learning,Rendering equation,Anti-aliasing,Computer vision,Path tracing,Rendering (computer graphics),Machine learning | Conference | 978-1-4503-5809-5 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Keller | 1 | 1861 | 180.65 |
| Jaroslav Krivánek | 2 | 290 | 21.61 |
| Jan Novák | 3 | 286 | 17.42 |
| Anton S. Kaplanyan | 4 | 23 | 3.14 |
| Marco Salvi | 5 | 98 | 6.80 |