Moritz Böhle (PhD Student)

MSc Moritz Daniel Böhle

Address: Max-Planck-Institut für Informatik
Saarland Informatics Campus
Campus E1 4
66123 Saarbrücken
Location: E1 4 - 622
Phone: +49 681 9325 2000
Fax: +49 681 9325 2099
E-mail: Get email via email

Personal Information

Publications

2023

Conference paper

D2

S. Rao, M. Böhle, A. Parchami-Araghi, and B. Schiele

“Studying How to Efficiently and Effectively Guide Models with Explanations,” in IEEE/CVF International Conference on Computer Vision (ICCV 2023), Paris, France, 2023.

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BibTeX

@inproceedings{Rao_ICCV23,
TITLE = {Studying How to Efficiently and Effectively Guide Models with Explanations},
AUTHOR = {Rao, Sukrut and B{\"o}hle, Moritz and Parchami-Araghi, Amin and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {979-8-3503-0718-4},
DOI = {10.1109/ICCV51070.2023.00184},
PUBLISHER = {IEEE},
YEAR = {2023},
MARGINALMARK = {$\bullet$},
DATE = {2023},
BOOKTITLE = {IEEE/CVF International Conference on Computer Vision (ICCV 2023)},
PAGES = {1922--1933},
ADDRESS = {Paris, France},
}

Endnote

%0 Conference Proceedings
%A Rao, Sukrut
%A B&#246;hle, Moritz
%A Parchami-Araghi, Amin
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Studying How to Efficiently and Effectively Guide Models with Explanations : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000D-CA7B-6
%R 10.1109/ICCV51070.2023.00184
%D 2023
%B IEEE/CVF International Conference on Computer Vision
%Z date of event: 2023-10-02 - 2023-10-06
%C Paris, France
%B IEEE/CVF International Conference on Computer Vision
%P 1922 - 1933
%I IEEE
%@ 979-8-3503-0718-4

2022

Conference paper

D2

M. Böhle, M. Fritz, and B. Schiele

“B-cos Networks: Alignment is All We Need for Interpretability,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 2022.

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BibTeX

@inproceedings{Boehle_CVPR2022,
TITLE = {B-cos Networks: {A}lignment is All We Need for Interpretability},
AUTHOR = {B{\"o}hle, Moritz and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-6946-3},
DOI = {10.1109/CVPR52688.2022.01008},
PUBLISHER = {IEEE},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)},
PAGES = {10319--10328},
ADDRESS = {New Orleans, LA, USA},
}

Endnote

%0 Conference Proceedings
%A B&#246;hle, Moritz
%A Fritz, Mario
%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 B-cos Networks: Alignment is All We Need for Interpretability : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000A-6F96-1
%R 10.1109/CVPR52688.2022.01008
%D 2022
%B 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition
%Z date of event: 2022-06-19 - 2022-06-24
%C New Orleans, LA, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 10319 - 10328
%I IEEE
%@ 978-1-6654-6946-3

Conference paper

D4D2

S. Rao, M. Böhle, and B. Schiele

“Towards Better Understanding Attribution Methods,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 2022.

more

BibTeX

@inproceedings{Rao_CVPR2022,
TITLE = {Towards Better Understanding Attribution Methods},
AUTHOR = {Rao, Sukrut and B{\"o}hle, Moritz and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-6946-3},
DOI = {10.1109/CVPR52688.2022.00998},
PUBLISHER = {IEEE},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)},
PAGES = {10213--10222},
ADDRESS = {New Orleans, LA, USA},
}

Endnote

%0 Conference Proceedings
%A Rao, Sukrut
%A B&#246;hle, Moritz
%A Schiele, Bernt
%+ Computer Graphics, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Towards Better Understanding Attribution Methods : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000A-6F91-6
%R 10.1109/CVPR52688.2022.00998
%D 2022
%B 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition
%Z date of event: 2022-06-19 - 2022-06-24
%C New Orleans, LA, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 10213 - 10222
%I IEEE
%@ 978-1-6654-6946-3

Article

D2

M. D. Böhle, M. Fritz, and B. Schiele

“Optimising for Interpretability: Convolutional Dynamic Alignment Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 6, 2022.

more

BibTeX

@article{Boehle2109.13004,
TITLE = {Optimising for Interpretability: Convolutional Dynamic Alignment Networks},
AUTHOR = {B{\"o}hle, Moritz Daniel and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISSN = {0162-8828},
DOI = {10.1109/TPAMI.2022.3226041},
PUBLISHER = {IEEE},
ADDRESS = {Piscataway, NJ},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
JOURNAL = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
VOLUME = {45},
NUMBER = {6},
PAGES = {7625--7638},
}

Endnote

%0 Journal Article
%A B&#246;hle, Moritz Daniel
%A Fritz, Mario
%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 Optimising for Interpretability: Convolutional Dynamic Alignment
  Networks : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0009-8113-F
%R 10.1109/TPAMI.2022.3226041
%7 2022
%D 2022
%J IEEE Transactions on Pattern Analysis and Machine Intelligence
%O IEEE Trans. Pattern Anal. Mach. Intell.
%V 45
%N 6
%& 7625
%P 7625 - 7638
%I IEEE
%C Piscataway, NJ
%@ false

2021

Conference paper

D2

M. D. Böhle, M. Fritz, and B. Schiele

“Convolutional Dynamic Alignment Networks for Interpretable Classifications,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, USA (Virtual), 2021.

more

BibTeX

@inproceedings{Boehle_CVPR21,
TITLE = {Convolutional Dynamic Alignment Networks for Interpretable Classifications},
AUTHOR = {B{\"o}hle, Moritz Daniel and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-4509-2},
DOI = {10.1109/CVPR46437.2021.00990},
PUBLISHER = {IEEE},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021)},
PAGES = {10029--10038},
ADDRESS = {Nashville, TN, USA (Virtual)},
}

Endnote

%0 Conference Proceedings
%A B&#246;hle, Moritz Daniel
%A Fritz, Mario
%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 Convolutional Dynamic Alignment Networks for Interpretable Classifications : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-1863-E
%R 10.1109/CVPR46437.2021.00990
%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 10029 - 10038
%I IEEE
%@ 978-1-6654-4509-2