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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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 |
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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 |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Wan, Renjie Shi, Boxin Li, Haoliang Duan, Ling-Yu Kot, Alex Chichung |
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Conference or Workshop Item |
author |
Wan, Renjie Shi, Boxin Li, Haoliang Duan, Ling-Yu Kot, Alex Chichung |
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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 |
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Reflection scene separation from a single image |
title_sort |
reflection scene separation from a single image |
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2022 |
url |
https://hdl.handle.net/10356/161801 https://openaccess.thecvf.com/menu |
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1745574664487305216 |