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Deepfovea: neural reconstruction for foveated rendering and video compression using learned natural video statistics

Published:28 July 2019Publication History

ABSTRACT

Recent advances in head-mounted displays (HMDs) provide new levels of immersion by delivering imagery straight to human eyes. The high spatial and temporal resolution requirements of these displays pose a tremendous challenge for real-time rendering and video compression. Since the eyes rapidly decrease in spatial acuity with increasing eccentricity, providing high resolution to peripheral vision is unnecessary. Upcoming VR displays provide real-time estimation of gaze, enabling gaze-contingent rendering and compression methods that take advantage of this acuity falloff. In this setting, special care must be given to avoid visible artifacts such as a loss of contrast or addition of flicker.

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References

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  • Published in

    cover image ACM Conferences
    SIGGRAPH '19: ACM SIGGRAPH 2019 Talks
    July 2019
    143 pages
    ISBN:9781450363174
    DOI:10.1145/3306307

    Copyright © 2019 Owner/Author

    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 28 July 2019

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    Overall Acceptance Rate1,822of8,601submissions,21%

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