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Adaptive Environment Sampling on CPU and GPU

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10386658" target="_blank" >RIV/00216208:11320/18:10386658 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1145/3214745.3214808" target="_blank" >https://doi.org/10.1145/3214745.3214808</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3214745.3214808" target="_blank" >10.1145/3214745.3214808</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Adaptive Environment Sampling on CPU and GPU

  • Original language description

    We present a production-ready approach for efficient environment light sampling which takes visibility into account. During a brief learning phase we cache visibility information in the camera space. The cache is then used to adapt the environment sampling strategy during the final rendering. Unlike existing approaches that account for visibility, our algorithm uses a small amount of memory, provides a lightweight sampling procedure that benefits even unoccluded scenes and, importantly, requires no additional artist care, such as manual setting of portals or other scene-specific adjustments. The technique is unbiased, simple to implement and integrate into a render engine. Its modest memory requirements and simplicity enable efficient CPU and GPU implementations that significantly improve the render times, especially in complex production scenes.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    ACM SIGGRAPH 2018 Talks

  • ISBN

    978-1-4503-5820-0

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    2

  • Pages from-to

  • Publisher name

    ASSOC COMPUTING MACHINERY

  • Place of publication

    NEW YORK

  • Event location

    Vancouver

  • Event date

    Aug 12, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000455248900068