Timezone: »
When we take photos through glass windows or doors, the transmitted background scene is often blended with undesirable reflection. Separating two layers apart to enhance the image quality is of vital importance for both human and machine perception. In this paper, we propose to exploit physical constraints from a pair of unpolarized and polarized images to separate reflection and transmission layers. Due to the simplified capturing setup, the system becomes more underdetermined compared with existing polarization based solutions that take three or more images as input. We propose to solve semireflector orientation estimation first to make the physical image formation well-posed and then learn to reliably separate two layers using a refinement network with gradient loss. Quantitative and qualitative experimental results show our approach performs favorably over existing polarization and single image based solutions.
Author Information
Youwei Lyu (Beijing University of Posts and Telecommunications)
Zhaopeng Cui (ETH Zurich)
Si Li (Beijing University of Posts and Telecommunications)
Marc Pollefeys (ETH Zurich)
Boxin Shi (Peking University)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Poster: Reflection Separation using a Pair of Unpolarized and Polarized Images »
Fri. Dec 13th 01:00 -- 03:00 AM Room East Exhibition Hall B + C #83
More from the Same Authors
-
2022 Spotlight: Neural Transmitted Radiance Fields »
Chengxuan Zhu · Renjie Wan · Boxin Shi -
2022 Poster: Neural Transmitted Radiance Fields »
Chengxuan Zhu · Renjie Wan · Boxin Shi -
2021 Oral: Shape As Points: A Differentiable Poisson Solver »
Songyou Peng · Chiyu Jiang · Yiyi Liao · Michael Niemeyer · Marc Pollefeys · Andreas Geiger -
2021 Poster: Shape As Points: A Differentiable Poisson Solver »
Songyou Peng · Chiyu Jiang · Yiyi Liao · Michael Niemeyer · Marc Pollefeys · Andreas Geiger -
2021 Poster: Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects »
Denys Rozumnyi · Martin R. Oswald · Vittorio Ferrari · Marc Pollefeys -
2021 Poster: Learning to dehaze with polarization »
Chu Zhou · Minggui Teng · Yufei Han · Chao Xu · Boxin Shi -
2020 Poster: Group Contextual Encoding for 3D Point Clouds »
Xu Liu · Chengtao Li · Jian Wang · Jingbo Wang · Boxin Shi · Xiaodong He -
2020 Poster: UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range Imaging »
Chu Zhou · Hang Zhao · Jin Han · Chang Xu · Chao Xu · Tiejun Huang · Boxin Shi -
2020 Poster: GPS-Net: Graph-based Photometric Stereo Network »
Zhuokun Yao · Kun Li · Ying Fu · Haofeng Hu · Boxin Shi -
2019 Poster: Learning from Bad Data via Generation »
Tianyu Guo · Chang Xu · Boxin Shi · Chao Xu · Dacheng Tao -
2017 Poster: Matching neural paths: transfer from recognition to correspondence search »
Nikolay Savinov · Lubor Ladicky · Marc Pollefeys -
2012 Poster: Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins »
Alex Schwing · Tamir Hazan · Marc Pollefeys · Raquel Urtasun -
2010 Poster: Gated Softmax Classification »
Roland Memisevic · Christopher Zach · Geoffrey E Hinton · Marc Pollefeys