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Title: Face image reflection removal
Authors: Wan, Renjie
Shi, Boxin
Li, Haoliang
Duan, Ling-Yu
Kot, Alex Chichung
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Wan, R., Shi, B., Li, H., Duan, L. & Kot, A. C. (2021). Face image reflection removal. International Journal of Computer Vision, 129(2), 385-399.
Journal: International Journal of Computer Vision
Abstract: Face images captured through glass are usually contaminated by reflections. The low-transmitted reflections make the reflection removal more challenging than for general scenes because important facial features would be completely occluded. In this paper, we propose and solve the face image reflection removal problem. We recover the important facial structures by incorporating inpainting ideas into a guided reflection removal framework, which takes two images as the input and considers various face-specific priors. We use a newly collected face reflection image dataset to train our model and compare with state-of-the-art methods. The proposed method shows advantages in estimating reflection-free face images for improving face recognition.
ISSN: 0920-5691
DOI: 10.1007/s11263-020-01372-5
Schools: School of Electrical and Electronic Engineering 
Research Centres: Rapid-Rich Object Search (ROSE) Lab 
Rights: © 2020 Springer Science+Business Media, LLC, part of Springer Nature.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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