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Newsletter #7 03/2023
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Hello to friends and family out there!

With newsletter #7 we are entering the home stretch of the KI Familie projects. It is probably the most interesting phase for the AI community as we are presenting more and more results of this unique cluster. One of the four projects - KI Absicherung - was already completed 2022, the three sister projects KI Delta Learning, KI Wissen, and KI Delta Tooling keep on working tirelessly, achieving milestone by milestone, and are about to prepare their final events in 2023.

In this edition, we look back to the second Open Project Day of KI Wissen, which took place at Fraunhofer in Sankt Augustin in January, focusing on the progress made in training efficiency by including already available knowledge and context data; and forth to KI Delta Learning – the next project to reach the finish line. The presentation of KI Delta Learning’s results is scheduled for March 9 (public day) and 10 (expert / family day). If you cannot make it to the Mercedes-Benz premises in Stuttgart-Vaihingen in March, join online (dial-in information below) or stay tuned for the next newsletter! Last but not least, KI Data Tooling reveals interesting project findings in the field of advanced AI training strategies… So please have a closer look and enjoy reading!

The KI Familie Editorial Team


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KI Wissen:
Second Turn of Open Project Days in Sankt Augustin

On January 17, 2023, the partners of the KI Familie projects (KI Wissen, KI Delta Learning, KI Data Tooling) have met to exchange information on efficient and knowledge-based AI systems. More than 90 attendees from industry, SMC and science took the opportunity to get an update on the overall project progress as well as to discuss details with partners directly and in person.
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Project Highlights

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KI Delta Learning: Final Event is Coming Closer

We are right in the middle of the preparations for the KI Delta Learning’s Final Event.
The Mercedes-Benz Campus in Stuttgart-Vaihingen will be the venue where dozens of project members from all over Germany will come together on March 9 and 10, 2023.
The event will focus on presenting the results of the BMWK funded research project in high-class talks, posters and presentations. The first day will be public and gives insights into the project’s key achievements on the path towards open world generalization. The second day is designed for members of the KI Familie to discuss the results in deep dives and to push for “transfer learning” within the cluster of fellow projects.
Have a look on the Agenda
For those who will not be able to attend on site, we offer the opportunity to join online via livestream. The dial-in information to the public presentation on March, 9 will be published via:

https://www.ki-deltalearning.de/final-event-livestream

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KI Delta Learning:

Work Package "Data Recording" Completed


One important development step of the KI Delta Learning project was completed successfully by the end of 2022: The recording of real driving data in Italy complemented the national data recording.

A test vehicle equipped with numerous sensors including cameras and lidar drove on pre-defined routes on public streets in Italy during November 2022. Prior to this driving experience and real data recording, many planning steps were taken.
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Picture: Deltas: New domains, complex situations require step-by-step extensions
©KI Delta Learning
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KI Data Tooling:

Creating a Data Kit for Advanced AI Training Strategies


Imagine having access to a digital replica of a real-world traffic scene that looks and behaves like the real thing. This is no longer a fantasy, as recent advances in computer graphics and simulation technologies have made it possible to create high-resolution digital twins of real traffic scenes. These digital twins are crucial for the development of next-level data-driven automated driving functions. The KI Data Tooling project is at the forefront of this development, creating a pioneering data kit comprising a high-quality dataset and a collection of realistic digital twins. What is s even more exciting is that the data kit includes both real and synthetic versions of the same scene, captured across all relevant sensor domains. With this data kit, the project aims to develop efficient and effective AI training strategies for the development of advanced automated driving functions.
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Events 2023

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VDA Technischer Kongress 2023

28.-29. March
Berlin, Germany
Find out more


EUCAD 2023
03.-04. May
Brussels, Belgium
Find out more


15th ITS European Congress
22.-24. May
Lisbon, Portugal
Find out more


TÜV safe.tech
23.-24. May
Munich, Germany
Find out more

Intelligent Vehicle Symposium
04.-07. June
Anchorage, Alaska
Find out more

CVPR 2023
Conference on Computer Vision and Pattern Recognition
18.-20. June
Vancouver, Canada
Find out more

ICPRS 2023
International Conference on Pattern Recognition Systems
04.-07. July
Guayaquil, Ecuador
Find out more

ARTS23
Automated Road Transportation Symposium
09.-13. July
San Francisco, USA
Find out more


ICECCME 2023
International Conference on Electrical, Computer, Communications and Mechatronics Engineering
19.-20. July
Tenerife, Canary Islands, Spain
Find out more

 

IAA Mobility 2023
05.-10. September
Munich, Germany
Find out more

Academic Corner - KI Familie Publications

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Domain Adaptation and Generalization: A Low-Complexity Approach
Joshua Niemeijer, Jörg P. Schäfer
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Heatmap-based Out-of-Distribution Detection
Julia Hornauer
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iOn the calibration of underrepresented classes in LiDAR-based semantic segmentation
Marielle Dreissig, Florian Piewak, Joschka Boedecker
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SynPeDS – A Synthetic Dataset for Pedestrian; Detection in Urban Traffic Scenes
Thomas Stauner,  Frederik Blank, Michael Fürst, Johannes Günther, Korbinian Hagn, Philipp Heidenreich, Markus Huber, Bastian Knerr, Thomas Schuli, Karl Leiss
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Towards Runtime Monitoring of Complex System Requirements for Autonomous Driving Functions
Dominik Grundt, Eike Möhlmann, Anna Köhne, Ishan Saxena, Ralf Stemmer, Bernd Westphal
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Suppress with a Patch: Revisiting Universal Adversarial Patch Attacks against Object Detection
Svetlana Pavlitskaya, Jonas Hendl, Sebastian Kleim, Leopold Johann Müller, Fabian Wylczoch, J.Marius Zöllner
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A Benchmark for Unsupervised Anomaly Detection in Multi-Agent Trajectories
Julian Wiederer, Julian Schmidt, Ulrich Kreßel, Klaus Dietmayer, Vasileios Belagiannis
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Adversarial Vulnerability of Temporal Feature Networks for Object Detection
Svetlana Pavlitskaya, Nikolai Polley, Michael Weber, J.Marius Zöllner
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An Unsupervised Domain Adaptive Approach for Multimodal 2D Object Detection in Adverse Weather Conditions
George Eskandar, Robert A. Marsden, Pavithran Pandiyan, Mario Döbler, Karim Guirguis, Bin Yang
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Validation of pedestrian detectors by classification of visual impairing factors
Korbinian Hagn, Oliver Grau
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Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects
Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk
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One Ontology to Rule Them All: Corner Case Scenarios for Autonomous Driving
Daniel Bogdoll
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A-Eye: Driving with the Eyes of AI for Corner Case Generation
Kamil Kowol, Prof. Stefan Bracke, Prof. Hanno Gottschalk
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SynPeDS – A Synthetic Dataset for Pedestrian; Detection in Urban Traffic Scenes
Thomas Stauner, Frederik Blank, Johannes Günther, Michael Fürst, Korbinian Hagn, Philipp Heidenreich, Markus Huber, Bastian Knerr, Thomas Schulik, Karl Leiss
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Infusing Contextual Knowledge Graphs for Visual Object Recognition
Sebastian Monka, Lavdim Halilaj
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Semi-supervised domain adaptation with CycleGAN guided by a downstream task loss
Annika Mütze, Matthias Rottmann, Hanno Gottschalk
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Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification 
Matthias Rottmann, Marco Reese
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Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection
Tobias Kalb, Björn Mauthe, Jürgen Beyerer
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Causes of Catastrophic Forgetting in Class-Incremental Semantic Segmentation
Tobias Kalb, Jürgen Beyerer
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