Jiangxin Dong (Post-Doc)
Dr. Jiangxin Dong
- Address
- Max-Planck-Institut für Informatik
Saarland Informatics Campus
Campus - Standort
- -
- Telefon
- +49 681 9325 0
- Fax
- +49 681 9325 2099
- Get email via email
Personal Information
Publications
Dong, J., & Pan, J. (2021). Deep Outlier Handling for Image Deblurring. IEEE Transactions on Image Processing, 30. doi:10.1109/TIP.2020.3048679
Export
BibTeX
@article{Dong2021,
TITLE = {Deep Outlier Handling for Image Deblurring},
AUTHOR = {Dong, Jiangxin and Pan, Jinshan},
LANGUAGE = {eng},
ISSN = {1057-7149},
DOI = {10.1109/TIP.2020.3048679},
PUBLISHER = {IEEE},
ADDRESS = {Piscataway, NJ},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
JOURNAL = {IEEE Transactions on Image Processing},
VOLUME = {30},
PAGES = {1799--1811},
}
Endnote
%0 Journal Article
%A Dong, Jiangxin
%A Pan, Jinshan
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
%T Deep Outlier Handling for Image Deblurring :
%G eng
%U http://hdl.handle.net/21.11116/0000-0007-F078-3
%R 10.1109/TIP.2020.3048679
%7 2021
%D 2021
%J IEEE Transactions on Image Processing
%V 30
%& 1799
%P 1799 - 1811
%I IEEE
%C Piscataway, NJ
%@ false
Dong, J., Roth, S., & Schiele, B. (2021). Learning Spatially-Variant MAP Models for Non-blind Image Deblurring. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021). Nashville, TN, USA (Virtual): IEEE. doi:10.1109/CVPR46437.2021.00485
Export
BibTeX
@inproceedings{Dong_CVPR21,
TITLE = {Learning Spatially-Variant {MAP} Models for Non-blind Image Deblurring},
AUTHOR = {Dong, Jiangxin and Roth, Stefan and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-4509-2},
DOI = {10.1109/CVPR46437.2021.00485},
PUBLISHER = {IEEE},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021)},
PAGES = {4886--4895},
ADDRESS = {Nashville, TN, USA (Virtual)},
}
Endnote
%0 Conference Proceedings
%A Dong, Jiangxin
%A Roth, Stefan
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Learning Spatially-Variant MAP Models for Non-blind Image Deblurring :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-157A-8
%R 10.1109/CVPR46437.2021.00485
%D 2021
%B 34th IEEE Conference on Computer Vision and Pattern Recognition
%Z date of event: 2021-06-19 - 2021-06-25
%C Nashville, TN, USA (Virtual)
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 4886 - 4895
%I IEEE
%@ 978-1-6654-4509-2
Dong, J., Roth, S., & Schiele, B. (2020). Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring. In Advances in Neural Information Processing Systems 33 (NeurIPS 2020). Virtual Event: Curran Associates, Inc.
Export
BibTeX
@inproceedings{Dong_NeurIPS20,
TITLE = {Deep {Wiener} Deconvolution: {Wiener} Meets Deep Learning for Image Deblurring},
AUTHOR = {Dong, Jiangxin and Roth, Stefan and Schiele, Bernt},
LANGUAGE = {eng},
PUBLISHER = {Curran Associates, Inc.},
YEAR = {2020},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {Advances in Neural Information Processing Systems 33 (NeurIPS 2020)},
EDITOR = {Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M. F. and Lin, H.},
ADDRESS = {Virtual Event},
}
Endnote
%0 Conference Proceedings
%A Dong, Jiangxin
%A Roth, Stefan
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring :
%G eng
%U http://hdl.handle.net/21.11116/0000-0007-A813-6
%D 2020
%B 34th Conference on Neural Information Processing Systems
%Z date of event: 2020-12-06 - 2020-12-12
%C Virtual Event
%B Advances in Neural Information Processing Systems 33
%E Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M. F.; Lin, H.
%I Curran Associates, Inc.
%U https://papers.nips.cc/paper/2020/file/0b8aff0438617c055eb55f0ba5d226fa-Paper.pdf