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NTIRE 2021 depth guided image relighting challenge

  • Majed El Helou
  • , Ruofan Zhou
  • , Sabine Susstrunk
  • , Radu Timofte
  • , Maitreya Suin
  • , A. N. Rajagopalan
  • , Yuanzhi Wang
  • , Tao Lu
  • , Yanduo Zhang
  • , Yuntao Wu
  • , Hao Hsiang Yang
  • , Wei Ting Chen
  • , Sy Yen Kuo
  • , Hao Lun Luo
  • , Zhiguang Zhang
  • , Zhipeng Luo
  • , Jianye He
  • , Zuo Liang Zhu
  • , Zhen Li
  • , Jia Xiong Qiu
  • Zeng Sheng Kuang, Cheng Ze Lu, Ming Ming Cheng, Xiu Li Shao, Chenghua Li, Bosong DIng, Wanli Qian, Fangya Li, Fu Li, Ruifeng Deng, Tianwei Lin, Songhua Liu, Xin Li, Dongliang He, Amirsaeed Yazdani, Tiantong Guo, Vishal Monga, Ntumba Elie Nsampi, Zhongyun Hu, Qing Wang, Sabari Nathan, Priya Kansal, Tongtong Zhao, Shanshan Zhao
  • EPFL
  • Swiss Federal Institute of Technology Zurich
  • Indian Institute of Technology Madras
  • Wuhan Institute of Technology
  • AsusTeK Computer Inc.
  • Ltd.
  • Nankai University
  • CAS - Institute of Automation
  • Baidu Inc
  • Pennsylvania State University
  • Northwestern Polytechnical University Xian
  • Couger Inc.
  • Dalian Maritime University

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

35 引文 斯高帕斯(Scopus)

摘要

Image relighting is attracting increasing interest due to its various applications. From a research perspective, im-age relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multiple direct uses for photo montage and aesthetic enhancement. In this paper, we review the NTIRE 2021 depth guided image relighting challenge.We rely on the VIDIT dataset for each of our two challenge tracks, including depth information. The first track is on one-to-one relighting where the goal is to transform the illumination setup of an input image (color temperature and light source position) to the target illumination setup. In the second track, the any-to-any relighting challenge, the objective is to transform the illumination settings of the in-put image to match those of another guide image, similar to style transfer. In both tracks, participants were given depth information about the captured scenes. We had nearly 250 registered participants, leading to 18 confirmed team sub-missions in the final competition stage. The competitions, methods, and final results are presented in this paper.

原文英語
主出版物標題Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
發行者IEEE Computer Society
頁面566-577
頁數12
ISBN(電子)9781665448994
DOIs
出版狀態已出版 - 06 2021
對外發佈是
事件2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, 美國
持續時間: 19 06 2021 → 25 06 2021

出版系列

名字IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN(列印)2160-7508
ISSN(電子)2160-7516

Conference

Conference2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
國家/地區美國
城市Virtual, Online
期間19/06/21 → 25/06/21

文獻附註

Publisher Copyright:
© 2021 IEEE.

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