David Stutz

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Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland University, Saarland Informatics CampusVerified email at mpi-inf.mpg.de
Matthias HeinProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
Bastian LeibeProfessor for Computer Vision, RWTH Aachen UniversityVerified email at vision.rwth-aachen.de
Yong GuoMax Planck Institute for InformaticsVerified email at mpi-inf.mpg.de
Andreas GeigerProfessor of Computer Science, University of Tübingen and Tübingen AI CenterVerified email at uni-tuebingen.de
Arnaud DoucetGoogle DeepMindVerified email at google.com
Ali Taylan CemgilResearch Scientist, DeepMind UKVerified email at google.com
Alexander HermansRWTH Aachen UniversityVerified email at vision.rwth-aachen.de
Nandhini ChandramoorthyIBM TJ Watson Research CenterVerified email at ibm.com
Sukrut RaoMax Planck Institute for Informatics, Saarland Informatics CampusVerified email at mpi-inf.mpg.de
Abhijit Guha RoyGoogle ResearchVerified email at google.com
Pushmeet KohliDeepMindVerified email at google.com
Jamie HayesGoogle DeepMindVerified email at google.com
Olivia WilesDeepMindVerified email at deepmind.com
Sven GowalDeepMindVerified email at deepmind.com
Max LoschPhD student, Max Planck Institute for InformaticsVerified email at mpi-inf.mpg.de
Mario FritzFaculty CISPA Helmholtz Center for Information Security; Professor Saarland UniversityVerified email at cispa.de
Adam FischGoogle DeepMindVerified email at google.com
Nenad TomasevGoogle DeepMindVerified email at google.com
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca

David Stutz

Research Scientist, DeepMind

Verified email at deepmind.com - Homepage

conformal prediction adversarial robustness adversarial examples deep learning computer vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Superpixels: An evaluation of the state-of-the-art D Stutz, A Hermans, B Leibe Computer Vision and Image Understanding 166, 1-27, 2018	589	2018
Disentangling adversarial robustness and generalization D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	315	2019
Understanding convolutional neural networks D Stutz Seminar Report, Visual Computing Institute, RWTH Aachen University, 2014	279*	2014
Learning 3d shape completion from laser scan data with weak supervision D Stutz, A Geiger Proceedings of the IEEE conference on computer vision and pattern …, 2018	257	2018
Confidence-calibrated adversarial training: Generalizing to unseen attacks D Stutz, M Hein, B Schiele International Conference on Machine Learning, 9155-9166, 2020	149	2020
Learning 3D Shape Completion Under Weak Supervision D Stutz, A Geiger International Journal of Computer Vision, 2018	103	2018
Adversarial training against location-optimized adversarial patches S Rao, D Stutz, B Schiele European conference on computer vision, 429-448, 2020	89	2020
Learning optimal conformal classifiers D Stutz, AT Cemgil, A Doucet arXiv preprint arXiv:2110.09192, 2021	71	2021
Relating adversarially robust generalization to flat minima D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF international conference on computer vision …, 2021	62	2021
Capabilities of gemini models in medicine K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ... arXiv preprint arXiv:2404.18416, 2024	59	2024
Superpixel segmentation: An evaluation D Stutz Pattern Recognition: 37th German Conference, GCPR 2015, Aachen, Germany …, 2015	47	2015
Bit error robustness for energy-efficient dnn accelerators D Stutz, N Chandramoorthy, M Hein, B Schiele Proceedings of Machine Learning and Systems 3, 569-598, 2021	38	2021
Superpixel segmentation using depth information D Stutz RWTH Aachen University, Aachen, Germany, 2014	25	2014
Robustifying token attention for vision transformers Y Guo, D Stutz, B Schiele Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023	19	2023
Random and adversarial bit error robustness: Energy-efficient and secure DNN accelerators D Stutz, N Chandramoorthy, M Hein, B Schiele IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3632-3647, 2022	16	2022
Improving robustness by enhancing weak subnets Y Guo, D Stutz, B Schiele European Conference on Computer Vision, 320-338, 2022	15	2022
Improving robustness of vision transformers by reducing sensitivity to patch corruptions Y Guo, D Stutz, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	14	2023
Learning Shape Completion from Bounding Boxes with CAD Shape Priors D Stutz RWTH Aachen University, 2017	14	2017
Neural Codes for Image Retrieval D Stutz Seminar Report, Visual Computing Institute, RWTH Aachen University, 2015	12	2015
Introduction to Neural Networks D Stutz Seminar Report, Human Language Technology and Pattern Recognition Group …, 2014	9	2014

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