1 citations · 3 across the 7 of their papers we have counts for
7 papers
SFG-ROS: A Resource-Aware Framework for Dense Multi-Agent Perception
Constantin Blessing, Elias Geiger, Jakob Häringer +2
Deploying heterogeneous multi-agent robot fleets for collaborative perception requires robust data exchange and scalable software architectures. However, standard ROS 2 implementat…
ARETE: Attention-based Rasterized Encoding for Topology Estimation using HSV-transformed Crowdsourced Vehicle Fleet Data
Daniel Fritz, Dimitrios Lagamtzis, Michael Mink +2
The continuous advancement of autonomous driving (AD) introduces challenges across multiple disciplines to ensure safe and efficient driving. One such challenge is the generation o…
Neural Rendering for Sensor Adaptation in 3D Object Detection
Felix Embacher, David Holtz, Jonas Uhrig +2
Autonomous vehicles often have varying camera sensor setups, which is inevitable due to restricted placement options for different vehicle types. Training a perception model on one…
StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception
Marcel Vosshans, Omar Ait-Aider, Youcef Mezouar +1
This paper presents StixelNExT++, a novel approach to scene representation for monocular perception systems. Building on the established Stixel representation, our method infers 3D…
Tiny Neural Networks for Multi-Object Tracking in a Modular Kalman Framework
Christian Alexander Holz, Christian Bader, Markus Enzweiler +1
We present a modular, production-ready approach that integrates compact Neural Network (NN) into a Kalmanfilter-based Multi-Object Tracking (MOT) pipeline. We design three tiny tas…
StixelNExT: Toward Monocular Low-Weight Perception for Object Segmentation and Free Space Detection
Marcel Vosshans, Omar Ait-Aider, Youcef Mezouar +1
In this work, we present a novel approach for general object segmentation from a monocular image, eliminating the need for manually labeled training data and enabling rapid, straig…
CoopScenes: Multi-Scene Infrastructure and Vehicle Data for Advancing Collective Perception in Autonomous Driving
Marcel Vosshans, Alexander Baumann, Matthias Drueppel +4
The increasing complexity of urban environments has underscored the potential of effective collective perception systems. To address these challenges, we present the CoopScenes dat…