D2
Computer Vision and Machine Learning

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

Personal Information

Publications

Böhle, M., Fritz, M., & Schiele, B. (2022). 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: IEEE. doi:10.1109/CVPR52688.2022.01008
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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 Böhle, 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
Rao, S., Böhle, M., & Schiele, B. (2022). Towards Better Understanding Attribution Methods. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022). New Orleans, LA, USA: IEEE. doi:10.1109/CVPR52688.2022.00998
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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 Böhle, 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
Böhle, M. D., Fritz, M., & Schiele, B. (2022). Optimising for Interpretability: Convolutional Dynamic Alignment Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2022.3226041
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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}, }
Endnote
%0 Journal Article %A Böhle, 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. %I IEEE %C Piscataway, NJ %@ false
Böhle, M. D., Fritz, M., & Schiele, B. (2021). Convolutional Dynamic Alignment Networks for Interpretable Classifications. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021). Nashville, TN, USA (Virtual): IEEE. doi:10.1109/CVPR46437.2021.00990
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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 Böhle, 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