SkyGAN: Towards Realistic Cloud Imagery for Image Based Lighting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10447099" target="_blank" >RIV/00216208:11320/22:10447099 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.2312/sr.20221151" target="_blank" >https://doi.org/10.2312/sr.20221151</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2312/sr.20221151" target="_blank" >10.2312/sr.20221151</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SkyGAN: Towards Realistic Cloud Imagery for Image Based Lighting

Popis výsledku v původním jazyce

Achieving photorealism when rendering virtual scenes in movies or architecture visualizations often depends on providing a realistic illumination and background. Typically, spherical environment maps serve both as a natural light source from the Sun and the sky, and as a background with clouds and a horizon. In practice, the input is either a static high-resolution HDR photograph manually captured on location in real conditions, or an analytical clear sky model that is dynamic, but cannot model clouds. Our approach bridges these two limited paradigms: a user can control the sun position and cloud coverage ratio, and generate a realistically looking environment map for these conditions. It is a hybrid data-driven analytical model based on a modified state-of-the-art GAN architecture, which is trained on matching pairs of physically-accurate clear sky radiance and HDR fisheye photographs of clouds. We demonstrate our results on renders of outdoor scenes under varying time, date, and cloud covers.

Název v anglickém jazyce

SkyGAN: Towards Realistic Cloud Imagery for Image Based Lighting

Popis výsledku anglicky

Achieving photorealism when rendering virtual scenes in movies or architecture visualizations often depends on providing a realistic illumination and background. Typically, spherical environment maps serve both as a natural light source from the Sun and the sky, and as a background with clouds and a horizon. In practice, the input is either a static high-resolution HDR photograph manually captured on location in real conditions, or an analytical clear sky model that is dynamic, but cannot model clouds. Our approach bridges these two limited paradigms: a user can control the sun position and cloud coverage ratio, and generate a realistically looking environment map for these conditions. It is a hybrid data-driven analytical model based on a modified state-of-the-art GAN architecture, which is trained on matching pairs of physically-accurate clear sky radiance and HDR fisheye photographs of clouds. We demonstrate our results on renders of outdoor scenes under varying time, date, and cloud covers.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF19_073%2F0016935" target="_blank" >EF19_073/0016935: Grantová schémata na UK</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Rendering 2022 - Symposium Track

ISBN

978-3-03868-187-8

ISSN

1727-3463

e-ISSN

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Počet stran výsledku

10

Strana od-do

13-22

Název nakladatele

The Eurographics Association

Místo vydání

Goslar, Germany

Místo konání akce

Prague

Datum konání akce

4. 7. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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