161 citations · 428 across the 24 of their papers we have counts for
5 papers · 1 filter
Mcity Data Engine: Iterative Model Improvement Through Open-Vocabulary Data Selection
Daniel Bogdoll, Rajanikant Patnaik Ananta, Abeyankar Giridharan +3
With an ever-increasing availability of data, it has become more and more challenging to select and label appropriate samples for the training of machine learning models. It is esp…
Conditioning Latent-Space Clusters for Real-World Anomaly Classification
Daniel Bogdoll, Svetlana Pavlitska, Simon Klaus +1
Anomalies in the domain of autonomous driving are a major hindrance to the large-scale deployment of autonomous vehicles. In this work, we focus on high-resolution camera data from…
From Model-Based to Data-Driven Simulation: Challenges and Trends in Autonomous Driving
Ferdinand Mütsch, Helen Gremmelmaier, Nicolas Becker +3
Simulation is an integral part in the process of developing autonomous vehicles and advantageous for training, validation, and verification of driving functions. Even though simula…
Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers
Daniel Bogdoll, Meng Zhang, Maximilian Nitsche +1
Great progress has been achieved in the community of autonomous driving in the past few years. As a safety-critical problem, however, anomaly detection is a huge hurdle towards a l…
Multimodal Detection of Unknown Objects on Roads for Autonomous Driving
Daniel Bogdoll, Enrico Eisen, Maximilian Nitsche +2
Tremendous progress in deep learning over the last years has led towards a future with autonomous vehicles on our roads. Nevertheless, the performance of their perception systems i…