33 citations · 54 across the 5 of their papers we have counts for
5 papers
Long Range Object-Level Monocular Depth Estimation for UAVs
David Silva, Nicolas Jourdan, Nils Gählert
Computer vision-based object detection is a key modality for advanced Detect-And-Avoid systems that allow for autonomous flight missions of UAVs. While standard object detection fr…
Identifying Out-of-Distribution Samples in Real-Time for Safety-Critical 2D Object Detection with Margin Entropy Loss
Yannik Blei, Nicolas Jourdan, Nils Gählert
Convolutional Neural Networks (CNNs) are nowadays often employed in vision-based perception stacks for safetycritical applications such as autonomous driving or Unmanned Aerial Veh…
On The Reliability Of Machine Learning Applications In Manufacturing Environments
Nicolas Jourdan, Sagar Sen, Erik Johannes Husom +3
The increasing deployment of advanced digital technologies such as Internet of Things (IoT) devices and Cyber-Physical Systems (CPS) in industrial environments is enabling the prod…
Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time
Nils Gählert, Jun-Jun Wan, Nicolas Jourdan +3
In this paper we propose a novel 3D single-shot object detection method for detecting vehicles in monocular RGB images. Our approach lifts 2D detections to 3D space by predicting a…
Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection
Nils Gählert, Nicolas Jourdan, Marius Cordts +2
Detecting vehicles and representing their position and orientation in the three dimensional space is a key technology for autonomous driving. Recently, methods for 3D vehicle detec…