Demo Data from VLDB 2026 / reviewers in the wild / expert
Ondrej Karlik
dblp:140/1122 · also Ondrej Karlík
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
3 papers |
Rendering · 93% Visualization and visual analytics · 7% | |
| Artificial intelligence
1 paper |
Probabilistic and Bayesian machine learning · 100% |
Topics — the 10 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering
global illumination |
0.6 | 2 | 2019 | MIS compensation: optimizing sampling techniques in multiple importance sampling · ACM Trans. Graph. 2019 Toward Evaluating the Usefulness of GlobalIllumination for Novices in Lighting Design Tasks · IEEE Trans. Vis. Comput. Graph. 2014 |
Rendering
monte carlo rendering |
0.6 | 2 | 2019 | MIS compensation: optimizing sampling techniques in multiple importance sampling · ACM Trans. Graph. 2019 On-line learning of parametric mixture models for light transport simulation · ACM Trans. Graph. 2014 |
Rendering › sampling
multiple importance sampling |
0.4 | 1 | 2019 | MIS compensation: optimizing sampling techniques in multiple importance sampling · ACM Trans. Graph. 2019 |
Rendering › light transport
path guiding |
0.4 | 1 | 2019 | MIS compensation: optimizing sampling techniques in multiple importance sampling · ACM Trans. Graph. 2019 |
Rendering › monte carlo rendering
importance sampling |
0.2 | 1 | 2014 | On-line learning of parametric mixture models for light transport simulation · ACM Trans. Graph. 2014 |
Rendering › lighting
lighting design |
0.2 | 1 | 2014 | Toward Evaluating the Usefulness of GlobalIllumination for Novices in Lighting Design Tasks · IEEE Trans. Vis. Comput. Graph. 2014 |
Rendering
light transport |
0.2 | 1 | 2014 | On-line learning of parametric mixture models for light transport simulation · ACM Trans. Graph. 2014 |
Visualization and visual analytics › visualization evaluation
user study |
0.2 | 1 | 2014 | Toward Evaluating the Usefulness of GlobalIllumination for Novices in Lighting Design Tasks · IEEE Trans. Vis. Comput. Graph. 2014 |
Machine learning › Probabilistic and Bayesian machine learning › structured models › latent variable model
mixture model |
0.1 | 1 | 2014 | On-line learning of parametric mixture models for light transport simulation · ACM Trans. Graph. 2014 |
Rendering › light transport
direct lighting |
0.1 | 1 | 2014 | Toward Evaluating the Usefulness of GlobalIllumination for Novices in Lighting Design Tasks · IEEE Trans. Vis. Comput. Graph. 2014 |
Methods — techniques the papers use, named apart from their topics
variance reduction · 0.4sampling density optimization · 0.4particle-based estimation · 0.4online learning · 0.4user study · 0.2parametric mixture models · 0.2parametric mixture model · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | MIS compensation: optimizing sampling techniques in multiple importance samplingabstractMultiple importance sampling (MIS) has become an indispensable tool in Monte Carlo rendering, widely accepted as a near-optimal solution for combining different sampling techniques. But an MIS combination, using the common balance or power heuristics, often results in an overly defensive estimator, leading to high variance. We show that by generalizing the MIS framework, variance can be substantially reduced. Specifically, we optimize one of the combined sampling techniques so as to decrease the overall variance of the resulting MIS estimator. We apply the approach to the computation of direct illumination due to an HDR environment map and to the computation of global illumination using a path guiding algorithm. The implementation can be as simple as subtracting a constant value from the tabulated sampling density done entirely in a preprocessing step. This produces a consistent noise reduction in all our tests with no negative influence on run time, no artifacts or bias, and no failure cases. Ondrej Karlik, Martin Sik, Petr Vévoda, Tomás Skrivan, Jaroslav Krivánek |
ACM Trans. Graph. | 1 |
| 2014 | On-line learning of parametric mixture models for light transport simulationabstractMonte Carlo techniques for light transport simulation rely on importance sampling when constructing light transport paths. Previous work has shown that suitable sampling distributions can be recovered from particles distributed in the scene prior to rendering. We propose to represent the distributions by a parametric mixture model trained in an on-line (i.e. progressive) manner from a potentially infinite stream of particles. This enables recovering good sampling distributions in scenes with complex lighting, where the necessary number of particles may exceed available memory. Using these distributions for sampling scattering directions and light emission significantly improves the performance of state-of-the-art light transport simulation algorithms when dealing with complex lighting. Jirí Vorba, Ondrej Karlik, Martin Sik, Tobias Ritschel 0001, Jaroslav Krivánek |
ACM Trans. Graph. | 2 |
| 2014 | Toward Evaluating the Usefulness of GlobalIllumination for Novices in Lighting Design TasksabstractThanks to its ability to improve the realism of computer-generated imagery, the use of global illumination has recently become widespread among digital lighting artists. It remains unclear, though, what impact it has on the lighting design workflows, especially for novice users. In this paper we present a user study which investigates the use of global illumination, large area lights, and non-physical fill lights in lighting design tasks, where 26 novice subjects design lighting with these tools. The collected data suggest that global illumination is not significantly harder to control for novice users that direct illumination, and when given the possibility, most users opt to use it in their designs. The use of global illumination together with large area lights leads to simpler lighting setups with fewer non-physical fill lights. Interestingly, global illumination does not supersede fill lights: users still include them into their globally illuminated lighting setups. We believe that our results will find use in the development of lighting design tools for non-expert users. Ondrej Karlik, Martin Ruzicka, Václav Gassenbauer, Fabio Pellacini, Jaroslav Krivánek |
IEEE Trans. Vis. Comput. Graph. | 1 |