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David Stutz
David Stutz
Research Scientist, DeepMind
Verified email at deepmind.com - Homepage
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
6092018
Disentangling adversarial robustness and generalization
D Stutz, M Hein, B Schiele
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
3322019
Understanding convolutional neural networks
D Stutz
Seminar Report, Visual Computing Institute, RWTH Aachen University, 2014
286*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
2702018
Confidence-calibrated adversarial training: Generalizing to unseen attacks
D Stutz, M Hein, B Schiele
International Conference on Machine Learning, 9155-9166, 2020
1572020
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
1232024
Learning 3D Shape Completion Under Weak Supervision
D Stutz, A Geiger
International Journal of Computer Vision, 2018
1072018
Adversarial training against location-optimized adversarial patches
S Rao, D Stutz, B Schiele
European conference on computer vision, 429-448, 2020
942020
Learning optimal conformal classifiers
D Stutz, AT Cemgil, A Doucet
arXiv preprint arXiv:2110.09192, 2021
862021
Relating adversarially robust generalization to flat minima
D Stutz, M Hein, B Schiele
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
672021
Superpixel segmentation: An evaluation
D Stutz
Pattern Recognition: 37th German Conference, GCPR 2015, Aachen, Germany …, 2015
472015
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
382021
Superpixel segmentation using depth information
D Stutz
RWTH Aachen University, Aachen, Germany, 2014
252014
Robustifying token attention for vision transformers
Y Guo, D Stutz, B Schiele
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
232023
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
182022
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
172023
Improving robustness by enhancing weak subnets
Y Guo, D Stutz, B Schiele
European Conference on Computer Vision, 320-338, 2022
172022
Imagen 3
J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, K Chan, Y Chen, ...
arXiv preprint arXiv:2408.07009, 2024
152024
Learning Shape Completion from Bounding Boxes with CAD Shape Priors
D Stutz
RWTH Aachen University, 2017
152017
Conformal prediction under ambiguous ground truth
D Stutz, AG Roy, T Matejovicova, P Strachan, AT Cemgil, A Doucet
arXiv preprint arXiv:2307.09302, 2023
132023
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