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Jonas Löhdefink
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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
532022
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
382021
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
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
312020
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
252020
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
112020
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
82020
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
52020
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
42022
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
32022
Improving performance of semantic segmentation CycleGANs by noise injection into the latent segmentation space
J Löhdefink, T Fingscheidt
arXiv preprint arXiv:2201.06415, 2022
22022
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
22022
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