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cs.CV2025
A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording
Philipp Reis, Joshua Ransiek, David Petri +2
High-quality datasets are essential for training robust perception systems in autonomous driving. However, real-world data collection is often biased toward common scenes and objec…
cs.CV2025
Data Quality Matters: Quantifying Image Quality Impact on Machine Learning Performance
Christian Steinhauser, Philipp Reis, Hubert Padusinski +2
Precise perception of the environment is essential in highly automated driving systems, which rely on machine learning tasks such as object detection and segmentation. Compression…
cs.CV2025
A Framework for a Capability-driven Evaluation of Scenario Understanding for Multimodal Large Language Models in Autonomous Driving
Tin Stribor Sohn, Philipp Reis, Maximilian Dillitzer +3
Multimodal large language models (MLLMs) hold the potential to enhance autonomous driving by combining domain-independent world knowledge with context-specific language guidance. T…