Philipp Benz
Orcid: 0000-0002-4389-8282
According to our database1,
Philipp Benz
authored at least 30 papers
between 2018 and 2024.
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Bibliography
2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Booster-SHOT: Boosting Stacked Homography Transformations for Multiview Pedestrian Detection with Attention.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
Knowledge Assembly: Semi-Supervised Multi-Task Learning from Multiple Datasets with Disjoint Labels.
CoRR, 2023
Noisy adversarial representation learning for effective and efficient image obfuscation.
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
2022
Booster-SHOT: Boosting Stacked Homography Transformations for Multiview Pedestrian Detection with Attention.
CoRR, 2022
Proceedings of the Workshop on Artificial Intelligence Safety 2022 (AISafety 2022) co-located with the Thirty-First International Joint Conference on Artificial Intelligence and the Twenty-Fifth European Conference on Artificial Intelligence (IJCAI-ECAI-2022), 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
CoRR, 2021
Towards Robust Data Hiding Against (JPEG) Compression: A Pseudo-Differentiable Deep Learning Approach.
CoRR, 2021
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Towards Robust Deep Hiding Under Non-Differentiable Distortions for Practical Blind Watermarking.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Batch Normalization Increases Adversarial Vulnerability and Decreases Adversarial Transferability: A Non-Robust Feature Perspective.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Batch Normalization Increases Adversarial Vulnerability: Disentangling Usefulness and Robustness of Model Features.
CoRR, 2020
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020
UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Fast Perception, Planning, and Execution for a Robotic Butler: Wheeled Humanoid M-Hubo.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019
Proceedings of the 30th British Machine Vision Conference 2019, 2019
2018
Proceedings of the 2018 IEEE International Conference on Big Data and Smart Computing, 2018