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A Categorized Reflection Removal Dataset with Diverse Real-world Scenes
[article]
2021
arXiv
pre-print
Due to the lack of a large-scale reflection removal dataset with diverse real-world scenes, many existing reflection removal methods are trained on synthetic data plus a small amount of real-world data, which makes it difficult to evaluate the strengths or weaknesses of different reflection removal methods thoroughly. Furthermore, existing real-world benchmarks and datasets do not categorize image data based on the types and appearances of reflection (e.g., smoothness, intensity), making it
arXiv:2108.03380v1
fatcat:let7e3bvgjh43k2pqih7fmz3bq