Veröffentlichungen
Artikel und Präsentationen aus dem Konsortium zum Projekt just better DATA
Veröffent-
lichungen
Artikel und Präsentationen aus dem Konsortium zum Projekt Just Better Data
Veröffentlichungen
- Daniel Bogdoll, Lukas Bosch, Tim Joseph, Helen Gremmelmaier, Yitian Yang, J. Marius Zöllner
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving
In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI) Philipp Rigoll, Jacob Langner, Eric Sax: Unveiling Objects with SOLA: An Annotation-Free Image Search on the Object Level for Automotive Data Sets, IEEE IV 2024, 04.-06.06.2024
Philipp Rigoll, Laurenz Adolph, Lennart Ries ,Eric Sax: CLIPping the Limits: Finding the Sweet Spot for Relevant Images in Automated Driving Systems Perception Testing , ITSC 2024, 24.-27. Sep. 2024
Daniel Bogdoll et al: AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving, Sept 2024
Daniel Bogdoll: MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations, Sept 2024
Marc Uecker Prof. Dr. J. Marius Zöllner: Can you see me now? Blind spot estimation for autonomous vehicles using scenario-based simulation with random reference sensors, IEEE IV 2024, Jeju, South Korea, 2.-5.6.2024
Philipp Reis, Philipp Rigoll, Eric Sax: Behavior Forests: Real-Time Discovery of Dynamic Behavior for Data Selection, Canada, Edmonton, 24.-27.9.2024
Daniel Bogdoll, Jan Imhof, Tim Joseph, J. Marius Zöllner: Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving, Conference on Robot Learning, Munich, 6.11.24
Daniel Bogdoll, Noël Ollick, Tim Joseph, J. Marius Zöllner: UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving, CoRL 2024, Munich, 6.11.24
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