30 citations · 46 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection
Di Feng, Zining Wang, Yiyang Zhou +5
The availability of many real-world driving datasets is a key reason behind the recent progress of object detection algorithms in autonomous driving. However, there exist ambiguity…
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty
Di Feng, Lars Rosenbaum, Fabian Timm +1
Reliable uncertainty estimation is crucial for robust object detection in autonomous driving. However, previous works on probabilistic object detection either learn predictive prob…
Inferring Spatial Uncertainty in Object Detection
Zining Wang, Di Feng, Yiyang Zhou +5
The availability of real-world datasets is the prerequisite for developing object detection methods for autonomous driving. While ambiguity exists in object labels due to error-pro…