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- W4308236851 abstract "Fusion-based quality assessment has emerged as a powerful method for developing high-performance quality models from quality models that individually achieve lower performances. A prominent example of such an algorithm is VMAF, which has been widely adopted as an industry standard for video quality prediction along with SSIM. In addition to advancing the state-of-the-art, it is imperative to alleviate the computational burden presented by the use of a heterogeneous set of quality models. In this paper, we unify atom quality models by computing them on a common transform domain that accounts for the Human Visual System, and we propose FUNQUE, a quality model that fuses unified quality evaluators. We demonstrate that in comparison to the state-of-the-art, FUNQUE offers significant improvements in both correlation against subjective scores and efficiency, due to computation sharing." @default.
- W4308236851 created "2022-11-09" @default.
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- W4308236851 date "2022-10-16" @default.
- W4308236851 modified "2023-10-14" @default.
- W4308236851 title "Funque: Fusion of Unified Quality Evaluators" @default.
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- W4308236851 doi "https://doi.org/10.1109/icip46576.2022.9897312" @default.
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