| Inspect, understand, overcome: A survey of practical methods for ai safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 68 | 2022 |
| An application-driven conceptualization of corner cases for perception in highly automated driving F Heidecker, J Breitenstein, K Rösch, J Löhdefink, M Bieshaar, C Stiller, ... 2021 IEEE Intelligent Vehicles Symposium (IV), 644-651, 2021 | 49 | 2021 |
| The vulnerability of semantic segmentation networks to adversarial attacks in autonomous driving: Enhancing extensive environment sensing A Bar, J Lohdefink, N Kapoor, SJ Varghese, F Huger, P Schlicht, ... IEEE Signal Processing Magazine 38 (1), 42-52, 2020 | 38 | 2020 |
| On low-bitrate image compression for distributed automotive perception: Higher peak snr does not mean better semantic segmentation J Löhdefink, A Bär, NM Schmidt, F Hüger, P Schlicht, T Fingscheidt 2019 IEEE Intelligent Vehicles Symposium (IV), 424-431, 2019 | 33* | 2019 |
| Self-supervised domain mismatch estimation for autonomous perception J Lohdefink, J Fehrling, M Klingner, F Huger, P Schlicht, NM Schmidt, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 25 | 2020 |
| Focussing learned image compression to semantic classes for V2X applications J Löhdefink, A Bär, NM Schmidt, F Hüger, P Schlicht, T Fingscheidt 2020 IEEE Intelligent Vehicles Symposium (IV), 1641-1648, 2020 | 13 | 2020 |
| Scalar and vector quantization for learned image compression: A study on the effects of MSE and GAN loss in various spaces J Löhdefink, F Hüger, P Schlicht, T Fingscheidt 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 8 | 2020 |
| Joint Prediction of Amodal and Visible Semantic Segmentation for Automated Driving J Breitenstein, J Löhdefink, T Fingscheidt European Conference on Computer Vision, 633-645, 2022 | 5 | 2022 |
| A self-supervised feature map augmentation (FMA) loss and combined augmentations finetuning to efficiently improve the robustness of CNNs N Kapoor, C Yuan, J Löhdefink, R Zimmerman, S Varghese, F Hüger, ... Proceedings of the 4th ACM Computer Science in Cars Symposium, 1-8, 2020 | 5 | 2020 |
| Adaptive bitrate quantization scheme without codebook for learned image compression J Löhdefink, J Sitzmann, A Bär, T Fingscheidt Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
| Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder A Bär, M Klingner, J Löhdefink, F Hüger, P Schlicht, T Fingscheidt Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
| Improving performance of semantic segmentation CycleGANs by noise injection into the latent segmentation space J Löhdefink, T Fingscheidt arXiv preprint arXiv:2201.06415, 2022 | 2 | 2022 |
Tim FingscheidtITG Fellow, Professor, Technische Universität Braunschweig, GermanyVerified email at tu-bs.de
