Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …

Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle
technology. Image based benchmark datasets have driven development in computer vision …

The ability to detect objects regardless of image distortions or weather conditions is crucial
for real-world applications of deep learning like autonomous driving. We here provide an …

Semantic scene understanding is crucial for robust and safe autonomous navigation,
particularly so in off-road environments. Recent deep learning advances for 3D semantic …

This article summarizes research trends on the topic of anomaly detection in video feeds of a
single scene. We discuss the various problem formulations, publicly available datasets and …

For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …

Humans drive in a holistic fashion which entails, in particular, understanding dynamic road
events and their evolution. Injecting these capabilities in autonomous vehicles can thus take …

Accurately detecting and tracking pedestrians in 3D space is challenging due to large
variations in rotations, poses and scales. The situation becomes even worse for dense …

Autonomous driving has rapidly developed and shown promising performance with recent
advances in hardware and deep learning methods. High-quality datasets are fundamental …