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, 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, British Machine Vision Conference Workshop, Glasgow,  27.11.24

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

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

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

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

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