Autonomous navigation requires structured representation of the road network and instance-
wise identification of the other traffic agents. Since the traffic scene is defined on the ground …

We address the problem of semantic nighttime image segmentation and improve the state-of-
the-art, by adapting daytime models to nighttime without using nighttime annotations …

Autonomous systems that operate in dynamic environments require robust object tracking in
3D as one of their key components. Most recent approaches for 3D multi-object tracking …

Abstract Knowledge of the road network topology is crucial for autonomous planning and
navigation. Yet, recovering such topology from a single image has only been explored in …

Autonomous navigation requires scene understanding of the action-space to move or
anticipate events. For planner agents moving on the ground plane, such as autonomous …

Forecasting the future behavior of all traffic agents in the vicinity is a key task to achieve safe
and reliable autonomous driving systems. It is a challenging problem as agents adjust their …

The local road network information is essential for autonomous navigation. This information
is commonly obtained from offline HD-Maps in terms of lane graphs. However, the local road …

Autonomous robots that can perform common tasks like driving, surveillance, and chores
have the biggest potential for impact due to frequency of usage, and the biggest potential for …

Speed-control forecasting, a challenging problem in driver behavior analysis, aims to predict
the future actions of a driver in controlling vehicle speed such as braking or acceleration. In …

Autonomous driving requires a structured understanding of the surrounding road network to
navigate. One of the most common and useful representation of such an understanding is …