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- W3136148639 abstract "Shooting video in 3D format can introduce stereoscopic artifacts, potentially causing viewers visual discomfort. In this work, we consider three common stereoscopic artifacts: color mismatch, sharpness mismatch, and geometric distortion. This paper introduces two neural-network-based methods for simultaneous color- and sharpness-mismatch estimation, as well as for estimating geometric distortions. To train these networks we prepared large datasets based on frames from full-length stereoscopic movies and compared the results with methods that previously served in analyses of full-length stereoscopic movies. We used our proposed methods to analyze 100 videos in VR180 format-a new format for stereoscopic videos in virtual reality (VR). This work presents overall results for these videos along with several examples of detected problems." @default.
- W3136148639 created "2021-03-29" @default.
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- W3136148639 date "2020-12-15" @default.
- W3136148639 modified "2023-09-24" @default.
- W3136148639 title "Neural-Network-Based Detection Methods for Color, Sharpness, and Geometry Artifacts in Stereoscopic and VR180 Videos" @default.
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- W3136148639 doi "https://doi.org/10.1109/ic3d51119.2020.9376385" @default.
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