Face Image Reflection Removal
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 reflecti...
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| Published in | International journal of computer vision Vol. 129; no. 2; pp. 385 - 399 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.02.2021
Springer Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| 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. |
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| AbstractList | 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. |
| Audience | Academic |
| Author | Duan, Ling-Yu Kot, Alex C. Shi, Boxin Wan, Renjie Li, Haoliang |
| Author_xml | – sequence: 1 givenname: Renjie orcidid: 0000-0002-0161-0367 surname: Wan fullname: Wan, Renjie email: rjwan@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University – sequence: 2 givenname: Boxin orcidid: 0000-0001-6749-0364 surname: Shi fullname: Shi, Boxin email: shiboxin@pku.edu.cn organization: National Engineering Laboratory for Video Technology, Department of CS, Peking University, Peng Cheng Laboratory – sequence: 3 givenname: Haoliang surname: Li fullname: Li, Haoliang organization: School of Electrical and Electronic Engineering, Nanyang Technological University – sequence: 4 givenname: Ling-Yu surname: Duan fullname: Duan, Ling-Yu organization: National Engineering Laboratory for Video Technology, Department of CS, Peking University, Peng Cheng Laboratory – sequence: 5 givenname: Alex C. surname: Kot fullname: Kot, Alex C. organization: School of Electrical and Electronic Engineering, Nanyang Technological University |
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| Keywords | Deep learning Optical flow Reflection removal Face images |
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