Jonas Löhdefink

According to our database, Jonas Löhdefink authored at least 13 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Improving Performance of Semantic Segmentation CycleGANs by Noise Injection into the Latent Segmentation Space.

Jonas Löhdefink, Tim Fingscheidt

CoRR, 2022

Joint Prediction of Amodal and Visible Semantic Segmentation for Automated Driving.

Jasmin Breitenstein, Jonas Löhdefink, Tim Fingscheidt

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Adaptive Bitrate Quantization Scheme Without Codebook for Learned Image Compression.

Jonas Löhdefink, Jonas Sitzmann, Andreas Bär, Tim Fingscheidt

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder.

Andreas Bär, Marvin Klingner, Jonas Löhdefink, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing.

Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

IEEE Signal Process. Mag., 2021

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety.

Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle

CoRR, 2021

An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving.

Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

2020

Focussing Learned Image Compression to Semantic Classes for V2X Applications.

Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Scalar and Vector Quantization for Learned Image Compression: A Study on the Effects of MSE and GAN Loss in Various Spaces.

Jonas Löhdefink, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Self-Supervised Domain Mismatch Estimation for Autonomous Perception.

Jonas Löhdefink, Justin Fehrling, Marvin Klingner, Fabian Hüger, Peter Schlicht, Nico M. Schmidt, Tim Fingscheidt

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs.

Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt

Proceedings of the CSCS '20: Computer Science in Cars Symposium, 2020

2019

GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation.

Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

CoRR, 2019

On Low-Bitrate Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation.

Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019