Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162627
Title: Benchmarking single-image reflection removal algorithms
Authors: Wan, Renjie
Shi, Boxin
Li, Haoliang
Hong, Yuchen
Duan, Ling-Yu
Kot, Alex Chichung
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Wan, R., Shi, B., Li, H., Hong, Y., Duan, L. & Kot, A. C. (2022). Benchmarking single-image reflection removal algorithms. IEEE Transactions On Pattern Analysis and Machine Intelligence, 3168560-. https://dx.doi.org/10.1109/TPAMI.2022.3168560
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
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 '`\sirp'' 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://sir2data.github.io/.
URI: https://hdl.handle.net/10356/162627
ISSN: 0162-8828
DOI: 10.1109/TPAMI.2022.3168560
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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