activity
20232026
most citedA Comprehensive Safety Metric to Evaluate Perception in Autonomous Systems

48 citations · 62 across the 14 of their papers we have counts for

collaborators
Showing cs.CVShow all

11 papers · 1 filter

cs.CV2026

Image Compression with Bubble-Aware Frame Rate Adaptation for Energy-Efficient Video Capsule Endoscopy

Oliver Bause, Jörg Gamerdinger, Julia Werner +1

Video Capsule Endoscopy (VCE) is a promising method for improving the medical examination of the small intestine in the gastrointestinal tract. A key challenge is their limited siz…

cs.CV2025

Criticality Metrics for Relevance Classification in Safety Evaluation of Object Detection in Automated Driving

Jörg Gamerdinger, Sven Teufel, Stephan Amann +1

Ensuring safety is the primary objective of automated driving, which necessitates a comprehensive and accurate perception of the environment. While numerous performance evaluation…

cs.CV2025

SnowyLane: Robust Lane Detection on Snow-covered Rural Roads Using Infrastructural Elements

Jörg Gamerdinger, Benedict Wetzel, Patrick Schulz +2

Lane detection for autonomous driving in snow-covered environments remains a major challenge due to the frequent absence or occlusion of lane markings. In this paper, we present a…

cs.CV2025

DenoiseCP-Net: Efficient Collective Perception in Adverse Weather via Joint LiDAR-Based 3D Object Detection and Denoising

Sven Teufel, Dominique Mayer, Jörg Gamerdinger +1

While automated vehicles hold the potential to significantly reduce traffic accidents, their perception systems remain vulnerable to sensor degradation caused by adverse weather an…

cs.CV2025

S2S-Net: Addressing the Domain Gap of Heterogeneous Sensor Systems in LiDAR-Based Collective Perception

Sven Teufel, Jörg Gamerdinger, Oliver Bringmann

Collective Perception (CP) has emerged as a promising approach to overcome the limitations of individual perception in the context of autonomous driving. Various approaches have be…

cs.CV2025

Datasets for Lane Detection in Autonomous Driving: A Comprehensive Review

Jörg Gamerdinger, Sven Teufel, Oliver Bringmann

Accurate lane detection is essential for automated driving, enabling safe and reliable vehicle navigation across a variety of road scenarios. Numerous datasets have been introduced…

cs.CV2024

MR3D-Net: Dynamic Multi-Resolution 3D Sparse Voxel Grid Fusion for LiDAR-Based Collective Perception

Sven Teufel, Jörg Gamerdinger, Georg Volk +1

The safe operation of automated vehicles depends on their ability to perceive the environment comprehensively. However, occlusion, sensor range, and environmental factors limit the…

cs.CV2024

SCOPE: A Synthetic Multi-Modal Dataset for Collective Perception Including Physical-Correct Weather Conditions

Jörg Gamerdinger, Sven Teufel, Patrick Schulz +3

Collective perception has received considerable attention as a promising approach to overcome occlusions and limited sensing ranges of vehicle-local perception in autonomous drivin…

cs.CV2024★ 2 cited

LSM: A Comprehensive Metric for Assessing the Safety of Lane Detection Systems in Autonomous Driving

Jörg Gamerdinger, Sven Teufel, Stephan Amann +2

Comprehensive perception of the vehicle's environment and correct interpretation of the environment are crucial for the safe operation of autonomous vehicles. The perception of sur…

cs.CV2024

Collective Perception Datasets for Autonomous Driving: A Comprehensive Review

Sven Teufel, Jörg Gamerdinger, Jan-Patrick Kirchner +2

To ensure safe operation of autonomous vehicles in complex urban environments, complete perception of the environment is necessary. However, due to environmental conditions, sensor…

cs.CV2023★ 6 cited

Collective PV-RCNN: A Novel Fusion Technique using Collective Detections for Enhanced Local LiDAR-Based Perception

Sven Teufel, Jörg Gamerdinger, Georg Volk +1

Comprehensive perception of the environment is crucial for the safe operation of autonomous vehicles. However, the perception capabilities of autonomous vehicles are limited due to…