Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161801
Title: Reflection scene separation from a single image
Authors: Wan, Renjie
Shi, Boxin
Li, Haoliang
Duan, Ling-Yu
Kot, Alex Chichung
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Wan, R., Shi, B., Li, H., Duan, L. & Kot, A. C. (2020). Reflection scene separation from a single image. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2395-2403. https://dx.doi.org/10.1109/CVPR42600.2020.00247
Project: NRF2016NRF-NSFC001-098 
NTU-PKU 
metadata.dc.contributor.conference: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Abstract: For images taken through glass, existing methods focus on the restoration of the background scene by regarding the reflection components as noise. However, the scene reflected by glass surface also contains important information to be recovered, especially for the surveillance or criminal investigations. In this paper, instead of removing reflection components from the mixture image, we aim at recovering reflection scenes from the mixture image. We first propose a strategy to obtain such ground truth and its corresponding input images. Then, we propose a two-stage framework to obtain the visible reflection scene from the mixture image. Specifically, we train the network with a shift-invariant loss which is robust to misalignment between the input and output images. The experimental results show that our proposed method achieves promising results.
URI: https://hdl.handle.net/10356/161801
URL: https://openaccess.thecvf.com/menu
ISBN: 978-1-7281-7168-5
DOI: 10.1109/CVPR42600.2020.00247
Schools: School of Electrical and Electronic Engineering 
Rights: © 2020 The Author(s). This CVPR 2020 paper is the Open Access version, provided by the Computer Vision Foundation.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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