Thomas Brunner

E-Mail:	t.brunner@tum.de
Google Scholar:	https://scholar.google.de/citations?user=FwCqwaoAAAAJ
LinkedIn:	https://www.linkedin.com/in/thomas-brunner-028b5687

Research

Have you seen this image before? Are you curious? [source]

My main area of research is Adversarial Examples for Neural Networks. Adversarial Examples are a fundamental problem observed in Deep Learning, and potentially a huge safety and security issue. Plus, they're a lot of fun to work with!

Thesis Topics

Currently I don't have any open topics. However, if you have a cool idea - just send me an email and we can work something out! Please include your CV and GitHub profile.

Publications

2020

Brendel, Wieland; Rauber, Jonas; Kurakin, Alexey; Papernot, Nicolas; Veliqi, Behar; Mohanty, Sharada P.; Laurent, Florian; Salathé, Marcel; Bethge, Matthias; Yu, Yaodong; Zhang, Hongyang; Xu, Susu; Zhang, Hongbao; Xie, Pengtao; Xing, Eric P.; Brunner, Thomas; Diehl, Frederik; Rony, Jérôme; Hafemann, Luiz Gustavo; Cheng, Shuyu; Dong, Yinpeng; Ning, Xuefei; Li, Wenshuo; Wang, Yu: Adversarial Vision Challenge. In: Escalera, Sergio; Herbrich, Ralf (Ed.): The NeurIPS '18 Competition. Springer International Publishing, 2020, 129-153 more…
Cheng, Chih-Hong; Huang, Chung-Hao; Brunner, Thomas; Hashemi, Vahid: Towards Safety Verification of Direct Perception Neural Networks. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), IEEE, 2020Grenoble, France, 1640-1643 more…

2019

Brunner, Thomas; Diehl, Frederik; Knoll, Alois: Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , 2019Long Beach, CA, USA more…
Brunner, Thomas; Diehl, Frederik; Truong Le, Michael; Knoll, Alois: Leveraging Semantic Embeddings for Safety-Critical Applications. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 2019Long Beach, CA, USA, 1389-1394 more…
Brunner, Thomas; Diehl, Frederik; Truong Le, Michael; Knoll, Alois: Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, 2019Seoul, South Korea, 4957-4965 more…
Frederik Diehl, Thomas Brunner, Michael Truong Le and Alois Knoll: Towards Graph Pooling by Edge Contraction. ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data, 2019 more…
Frederik Diehl, Thomas Brunner, Michael Truong Le, Alois Knoll: Graph Neural Networks for Modelling Traffic Participant Interaction. IEEE Intelligent Vehicles Symposium 2019, 2019 more…
Kessler, Tobias; Bernhard, Julian; Buechel, Martin; Esterle, Klemens; Hart, Patrick; Malovetz, Daniel; Truong Le, Michael; Diehl, Frederik; Brunner, Thomas; Knoll, Alois: Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving. 2019 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2019 more…

2018

Michael Truong Le, Frederik Diehl, Thomas Brunner, Alois Knoll: Uncertainty Estimation for Deep Neural Object Detectors in Safety-Critical Applications. International Conference on Intelligent Transportation Systems 2018, 2018 more…