5 papers
Rainy screens: Collecting rainy datasets, indoors
Horia Porav, Valentina-Nicoleta Musat, Tom Bruls +1
Acquisition of data with adverse conditions in robotics is a cumbersome task due to the difficulty in guaranteeing proper ground truth and synchronising with desired weather condit…
Don't Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation
Horia Porav, Tom Bruls, Paul Newman
Modern models that perform system-critical tasks such as segmentation and localization exhibit good performance and robustness under ideal conditions (i.e. daytime, overcast) but p…
Generating All the Roads to Rome: Road Layout Randomization for Improved Road Marking Segmentation
Tom Bruls, Horia Porav, Lars Kunze +1
Road markings provide guidance to traffic participants and enforce safe driving behaviour, understanding their semantic meaning is therefore paramount in (automated) driving. Howev…
I Can See Clearly Now : Image Restoration via De-Raining
Horia Porav, Tom Bruls, Paul Newman
We present a method for improving segmentation tasks on images affected by adherent rain drops and streaks. We introduce a novel stereo dataset recorded using a system that allows…
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping
Tom Bruls, Horia Porav, Lars Kunze +1
Many tasks performed by autonomous vehicles such as road marking detection, object tracking, and path planning are simpler in bird's-eye view. Hence, Inverse Perspective Mapping (I…