Markus Hillemann
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View article: Evaluation of Semi-supervised Semantic Segmentation for Remote Sensing, Medical Imaging, and Machine Vision Settings
Evaluation of Semi-supervised Semantic Segmentation for Remote Sensing, Medical Imaging, and Machine Vision Settings Open
Semi-supervised semantic segmentation (S4) has garnered significant attention in recent years due to the time-consuming and costly process of creating pixel-level annotations. Instead of only relying on labeled data, semi-supervised approa…
View article: FeatureGS: Eigenvalue-Feature Optimization in 3D Gaussian Splatting for Geometrically Accurate and Artifact-Reduced Reconstruction
FeatureGS: Eigenvalue-Feature Optimization in 3D Gaussian Splatting for Geometrically Accurate and Artifact-Reduced Reconstruction Open
3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their dir…
View article: SOS: Segment Object System for Open-World Instance Segmentation With Object Priors
SOS: Segment Object System for Open-World Instance Segmentation With Object Priors Open
We propose an approach for Open-World Instance Segmentation (OWIS), a task that aims to segment arbitrary unknown objects in images by generalizing from a limited set of annotated object classes during training. Our Segment Object System (…
View article: HoloGS: Instant Depth-based 3D Gaussian Splatting with Microsoft HoloLens 2
HoloGS: Instant Depth-based 3D Gaussian Splatting with Microsoft HoloLens 2 Open
In the fields of photogrammetry, computer vision and computer graphics, the task of neural 3D scene reconstruction has led to the exploration of various techniques. Among these, 3D Gaussian Splatting stands out for its explicit representat…
View article: Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications Open
Neural Radiance Fields (NeRFs) have become a rapidly growing research field with the potential to revolutionize typical photogrammetric workflows, such as those used for 3D scene reconstruction. As input, NeRFs require multi-view images wi…
View article: Uncertainty-aware Cross-Entropy for Semantic Segmentation
Uncertainty-aware Cross-Entropy for Semantic Segmentation Open
Deep neural networks have shown exceptional performance in various tasks, but their lack of robustness, reliability, and tendency to be overconfident pose challenges for their deployment in safety-critical applications like autonomous driv…
View article: Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation Open
The estimation of 6D object poses is a fundamental task in many computer vision applications. Particularly, in high risk scenarios such as human-robot interaction, industrial inspection, and automation, reliable pose estimates are crucial.…
View article: A Comparative Study on Multi-task Uncertainty Quantification in Semantic Segmentation and Monocular Depth Estimation
A Comparative Study on Multi-task Uncertainty Quantification in Semantic Segmentation and Monocular Depth Estimation Open
Deep neural networks excel in perception tasks such as semantic segmentation and monocular depth estimation, making them indispensable in safety-critical applications like autonomous driving and industrial inspection. However, they often s…
View article: Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications Open
Neural Radiance Fields (NeRFs) have become a rapidly growing research field with the potential to revolutionize typical photogrammetric workflows, such as those used for 3D scene reconstruction. As input, NeRFs require multi-view images wi…
View article: HoloGS: Instant Depth-based 3D Gaussian Splatting with Microsoft HoloLens 2
HoloGS: Instant Depth-based 3D Gaussian Splatting with Microsoft HoloLens 2 Open
In the fields of photogrammetry, computer vision and computer graphics, the task of neural 3D scene reconstruction has led to the exploration of various techniques. Among these, 3D Gaussian Splatting stands out for its explicit representat…
View article: DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation Open
The intersection of deep learning and photogrammetry unveils a critical need for balancing the power of deep neural networks with interpretability and trustworthiness, especially for safety-critical application like autonomous driving, med…
View article: Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation Open
The estimation of 6D object poses is a fundamental task in many computer vision applications. Particularly, in high risk scenarios such as human-robot interaction, industrial inspection, and automation, reliable pose estimates are crucial.…
View article: Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation Open
Quantifying the predictive uncertainty emerged as a possible solution to common challenges like overconfidence or lack of explainability and robustness of deep neural networks, albeit one that is often computationally expensive. Many real-…
View article: SEGMENTATION OF INDUSTRIAL BURNER FLAMES: A COMPARATIVE STUDY FROM TRADITIONAL IMAGE PROCESSING TO MACHINE AND DEEP LEARNING
SEGMENTATION OF INDUSTRIAL BURNER FLAMES: A COMPARATIVE STUDY FROM TRADITIONAL IMAGE PROCESSING TO MACHINE AND DEEP LEARNING Open
In many industrial processes, such as power generation, chemical production, and waste management, accurately monitoring industrial burner flame characteristics is crucial for safe and efficient operation. A key step involves separating th…
View article: U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation Open
Deep neural networks have shown exceptional performance in various tasks, but their lack of robustness, reliability, and tendency to be overconfident pose challenges for their deployment in safety-critical applications like autonomous driv…
View article: DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation Open
Deep neural networks lack interpretability and tend to be overconfident, which poses a serious problem in safety-critical applications like autonomous driving, medical imaging, or machine vision tasks with high demands on reliability. Quan…
View article: Segmentation of Industrial Burner Flames: A Comparative Study from Traditional Image Processing to Machine and Deep Learning
Segmentation of Industrial Burner Flames: A Comparative Study from Traditional Image Processing to Machine and Deep Learning Open
In many industrial processes, such as power generation, chemical production, and waste management, accurately monitoring industrial burner flame characteristics is crucial for safe and efficient operation. A key step involves separating th…
View article: EVALUATION OF SELF-SUPERVISED LEARNING APPROACHES FOR SEMANTIC SEGMENTATION OF INDUSTRIAL BURNER FLAMES
EVALUATION OF SELF-SUPERVISED LEARNING APPROACHES FOR SEMANTIC SEGMENTATION OF INDUSTRIAL BURNER FLAMES Open
In recent years, self-supervised learning has made tremendous progress in closing the gap to supervised learning due to the rapid development of more sophisticated approaches like SimCLR, MoCo, and SwAV. However, these achievements are pri…
View article: COMPARISON OF UNCERTAINTY QUANTIFICATION METHODS FOR CNN-BASED REGRESSION
COMPARISON OF UNCERTAINTY QUANTIFICATION METHODS FOR CNN-BASED REGRESSION Open
The evaluation of reliability is not only of high importance for safety-critical deep learning applications but for object pose estimation as well. The uncertainty of the result is one way to express its reliability. In order to better und…
View article: IMPACT OF DIFFERENT TRAJECTORIES ON EXTRINSIC SELF-CALIBRATION FOR VEHICLE-BASED MOBILE LASER SCANNING SYSTEMS
IMPACT OF DIFFERENT TRAJECTORIES ON EXTRINSIC SELF-CALIBRATION FOR VEHICLE-BASED MOBILE LASER SCANNING SYSTEMS Open
The extrinsic calibration of a Mobile Laser Scanning system aims to determine the relative orientation between a laser scanner and a sensor that estimates the exterior orientation of the sensor system. The relative orientation is one compo…
View article: Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features
Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features Open
Mobile Mapping is an efficient technology to acquire spatial data of the environment. The spatial data is fundamental for applications in crisis management, civil engineering or autonomous driving. The extrinsic calibration of the Mobile M…
View article: COMBINING INDEPENDENT VISUALIZATION AND TRACKING SYSTEMS FOR AUGMENTED REALITY
COMBINING INDEPENDENT VISUALIZATION AND TRACKING SYSTEMS FOR AUGMENTED REALITY Open
The basic requirement for the successful deployment of a mobile augmented reality application is a reliable tracking system with high accuracy. Recently, a helmet-based inside-out tracking system which meets this demand has been proposed f…
View article: POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS
POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS Open
In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular…
View article: UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF AMULTI-CAMERA-SYSTEM AND A LASERSCANNER
UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF AMULTI-CAMERA-SYSTEM AND A LASERSCANNER Open
Unmanned Aerial Vehicle (UAV) with adequate sensors enable new applications in the scope between expensive, large-scale, aircraftcarried remote sensing and time-consuming, small-scale, terrestrial surveyings. To perform these applications,…