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

  1. 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)

  2. 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 // SOLA_master: An application implemented in Python for searching image data sets in the automotive domain

  3. 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

  4. Daniel Bogdoll et al: AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving, Sept 2024

  5. Daniel Bogdoll: MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations, Sept 2024

  6. Marc Uecker, 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

  7. Philipp Reis, Philipp Rigoll, Eric Sax: Behavior Forests: Real-Time Discovery of Dynamic Behavior for Data Selection, Canada, Edmonton, 24.-27.9.2024

  8. Daniel Bogdoll, Jan Imhof, Tim Joseph, J. Marius Zöllner: Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving, British Machine Vision Conference Workshop, Glasgow,  27.11.24

  9. Daniel Bogdoll, Noël Ollick, Tim Joseph, Svetlana Pavlitska, Marius Zöllner: UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving, British Machine Vision Conference Workshop, Glasgow,  27.11.24

  10. Pascal Zwick, Kevin Rösch, Marvin Klemp, and Oliver Bringmann: Context-Aware Full Body Anonymization using Text-to-Image Diffusion Models, European Conference on Computer Vision ECCV, Mailand, 29.09.24

  11. Youssef Shoeb, Nazir Nayal, Azarm Nowzard, Fatma Güney, Hanno Gottschalk: Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios, Porto, Portugal, 26.2.25

  12. Nazir Nayal, Youssef Shoeb, Fatma Güney: A Likelihood Ratio-Based Approach to Segmenting Unknown Objects, International Journal of Computer Vision (IJCV), 2024

  13. Robert Aufschläger, Sebastian Wilhelm, Michael Heigl, Martin Schramm: ClustEm4Ano: Clustering Text Embeddings of Nominal Textual Attributes for Microdata Anonymization, IDEAS 2024, Bayonne, France, 27.8.24

  14. Shoeb_ASPAI_2025 ShoebNowzadGottschalkMonitoringOoDPrediction_ASPAI_2025 Error in Semantic Segmentation Networks via Temporal Consistency of Logits, ASPAI 2025, Innsbruck, Austria, 7.4.25

  15. Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk: Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art, CVPRW, Colorado, USA, 11.6.25

  16. Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk: Adaptive Neural Networks for Intelligent Data-Driven Development, IEEE Intelligent Vehicles Symposium (IV), Cluj, Romania, 22.6.25

  17. Daniel Bogdoll, Finn Sartoris, Vincent Geppert, Svetlana Pavlitska, J. Marius Zöllner: Label-Free Model Failure Detection for Lidar-based Point Cloud Segmentation, IEEE Intelligent Vehicles Symposium (IV), Cluj, Romania, 22.6.25

  18. Robert Aufschläger, Youssef Shoeb, Azarm Nowzad, Fabian Bally: Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence, IEEE ITSC 2025, Gold Coast, Australia, 18.-21.11.25

  19. Michael Schötz, Fabian Bally, Patrick Kühnel, Martina Schöll, Thomas Limbrunner: Smart Data Capture in ADAS Development and Validation: Leveraging Lambda Triggers and Edge Computing for Selective Recording, IAVVC 2025, Baden-Baden, Germany, 1.10.25

  20. Youssef Shoeb, Alaeddin Abdellaoui, Azarm Nowzad, Hanno Gottschalk: Scene-Level Triggers Using Foundation Model Embedding Scene-Level Triggers Using Foundation Model Embeddingss, IAVVC 2025, Baden-Baden, Germany, 1.10.25
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