학술논문
NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results
Document Type
Conference
Author
Abuolaim, Abdullah; Timofte, Radu; Brown, Michael S.; Zhang, Dafeng; Wang, Xiaobing; Zamir, Syed Waqas; Arora, Aditya; Khan, Salman; Hayat, Munawar; Khan, Fahad Shahbaz; Shao, Ling; Liu, Shuai; Lei, Lei; Feng, Chaoyu; Xiong, Zhiwei; Xiao, Zeyu; Xu, Ruikang; Zhu, Yunan; Liu, Dong; Vo, Tu; Miao, Si; Shah, Nisarg A.; Liang, Pengwei; Zhong, Zhiwei; Hu, Xingyu; Chen, Yiqun; Li, Chenghua; Bai, Xiaoying; Zhang, Chi; Yao, Yiheng; Gang, Ruipeng; Nathan, Sabari; Ragavendran, Thangavelu; Srinija, Venkatakrishnan; Srivatsav, Venkatakrishnan
Source
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 IEEE/CVF Conference on. :578-587 Jun, 2021
Subject
Language
ISSN
2160-7516
Abstract
This paper provides a review of the NTIRE 2021 challenge targeting defocus deblurring using dual-pixel (DP) data. The goal of this single-track challenge was to reduce spatially varying defocus blur present in images captured with a shallow depth of field. The images used in this challenge were obtained using a DP sensor that provided a pair of DP views per captured image. Submitted solutions were evaluated using conventional signal processing metrics, namely peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Out of 185 registered participants, nine teams provided methods and competed in the final stage. The paper describes the methods proposed by the participating teams and their results. The winning teams represent the state-of-the-art in terms of defocus de-blurring using DP images.