Reflection scene separation from a single image

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 investigat...

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Main Authors: Wan, Renjie, Shi, Boxin, Li, Haoliang, Duan, Ling-Yu, Kot, Alex Chichung
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/161801
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1618012022-09-20T07:41:43Z Reflection scene separation from a single image Wan, Renjie Shi, Boxin Li, Haoliang Duan, Ling-Yu Kot, Alex Chichung School of Electrical and Electronic Engineering 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Engineering::Electrical and electronic engineering Reflection Computer Vision 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. National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore, under the NRFNSFC grant NRF2016NRF-NSFC001-098 and NTU-PKU Joint Research Institute with donation from Ng Teng Fong Charitable Foundation. The research work was done at the Rapid-Rich Object Search (ROSE) Lab, Nanyang Technological University, Singapore. This research is in part supported by the National Natural Science Foundation of China under Grants U1611461 and 61872012, National Key R&D Program of China (2019YFF0302902), Shenzhen Municipal Science and Technology Program under Grant JCYJ20170818141146428, and Beijing Academy of Artificial Intelligence (BAAI). 2022-09-20T06:31:22Z 2022-09-20T06:31:22Z 2020 Conference Paper 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 978-1-7281-7168-5 https://hdl.handle.net/10356/161801 10.1109/CVPR42600.2020.00247 2-s2.0-85094863642 https://openaccess.thecvf.com/menu 2395 2403 en NRF2016NRF-NSFC001-098 NTU-PKU © 2020 The Author(s). This CVPR 2020 paper is the Open Access version, provided by the Computer Vision Foundation. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Reflection
Computer Vision
spellingShingle Engineering::Electrical and electronic engineering
Reflection
Computer Vision
Wan, Renjie
Shi, Boxin
Li, Haoliang
Duan, Ling-Yu
Kot, Alex Chichung
Reflection scene separation from a single image
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Wan, Renjie
Shi, Boxin
Li, Haoliang
Duan, Ling-Yu
Kot, Alex Chichung
format Conference or Workshop Item
author Wan, Renjie
Shi, Boxin
Li, Haoliang
Duan, Ling-Yu
Kot, Alex Chichung
author_sort Wan, Renjie
title Reflection scene separation from a single image
title_short Reflection scene separation from a single image
title_full Reflection scene separation from a single image
title_fullStr Reflection scene separation from a single image
title_full_unstemmed Reflection scene separation from a single image
title_sort reflection scene separation from a single image
publishDate 2022
url https://hdl.handle.net/10356/161801
https://openaccess.thecvf.com/menu
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