8 citations · 10 across the 5 of their papers we have counts for
5 papers
Can Transformer Attention Spread Give Insights Into Uncertainty of Detected and Tracked Objects?
Felicia Ruppel, Florian Faion, Claudius Gläser +1
Transformers have recently been utilized to perform object detection and tracking in the context of autonomous driving. One unique characteristic of these models is that attention…
Transformers for Object Detection in Large Point Clouds
Felicia Ruppel, Florian Faion, Claudius Gläser +1
We present TransLPC, a novel detection model for large point clouds that is based on a transformer architecture. While object detection with transformers has been an active field o…
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars
Florian Drews, Di Feng, Florian Faion +3
We propose DeepFusion, a modular multi-modal architecture to fuse lidars, cameras and radars in different combinations for 3D object detection. Specialized feature extractors take…
Understanding the Domain Gap in LiDAR Object Detection Networks
Jasmine Richter, Florian Faion, Di Feng +3
In order to make autonomous driving a reality, artificial neural networks have to work reliably in the open-world. However, the open-world is vast and continuously changing, so it…
Three-dimensional Simultaneous Shape and Pose Estimation for Extended Objects Using Spherical Harmonics
Gerhard Kurz, Florian Faion, Florian Pfaff +2
We propose a new recursive method for simultaneous estimation of both the pose and the shape of a three-dimensional extended object. The key idea of the presented method is to repr…