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- W4226020516 abstract "Reflection removal has been discussed for more than decades. This paper aims to provide the analysis for different reflection properties and factors that influence image formation, an up-to-date taxonomy for existing methods, a benchmark dataset, and the unified benchmarking evaluations for state-of-the-art (especially learning-based) methods. Specifically, this paper presents a SIngle-image Reflection Removal Plus dataset SIR 2+ with the new consideration for in-the-wild scenarios and glass with diverse color and unplanar shapes. We further perform quantitative and visual quality comparisons for state-of-the-art single-image reflection removal algorithms. Open problems for improving reflection removal algorithms are discussed at the end. Our dataset and follow-up update can be found at https://reflectionremoval.github.io/sir2data/." @default.
- W4226020516 created "2022-05-05" @default.
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- W4226020516 date "2023-02-01" @default.
- W4226020516 modified "2023-10-14" @default.
- W4226020516 title "Benchmarking Single-Image Reflection Removal Algorithms" @default.
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- W4226020516 doi "https://doi.org/10.1109/tpami.2022.3168560" @default.
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