30 citations · 50 across the 9 of their papers we have counts for
14 papers
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…
A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding
Di Feng, Yiyang Zhou, Chenfeng Xu +2
Detecting dynamic objects and predicting static road information such as drivable areas and ground heights are crucial for safe autonomous driving. Previous works studied each perc…
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…
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
Di Feng, Ali Harakeh, Steven Waslander +1
Capturing uncertainty in object detection is indispensable for safe autonomous driving. In recent years, deep learning has become the de-facto approach for object detection, and ma…
Deep Detection for Face Manipulation
Disheng Feng, Xuequan Lu, Xufeng Lin
It has become increasingly challenging to distinguish real faces from their visually realistic fake counterparts, due to the great advances of deep learning based face manipulation…