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Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
As input, NeRFs require multi-view images with corresponding camera poses as well as the interior orientation.
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation
In this work, we propose a method to quantify the uncertainty of multi-stage 6D object pose estimation approaches with deep ensembles.
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation
By implicitly leveraging the predictive uncertainties of the teacher, EMUFormer achieves new state-of-the-art results on Cityscapes and NYUv2 and additionally estimates high-quality predictive uncertainties for both tasks that are comparable or superior to a Deep Ensemble despite being an order of magnitude more efficient.
Sensitivity analysis of AI-based algorithms for autonomous driving on optical wavefront aberrations induced by the windshield
To address this issue, this paper investigates the domain shift problem further by evaluating the sensitivity of two perception models to different windshield configurations.
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation
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 driving.
Segmentation of Industrial Burner Flames: A Comparative Study from Traditional Image Processing to Machine and Deep Learning
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.
Windscreen Optical Quality for AI Algorithms: Refractive Power and MTF not Sufficient
Further, as the industry is moving towards the modulation transfer function (MTF) as an alternative, we mathematically show that this metric cannot be used on windscreens alone, but that the windscreen forms a novel optical system together with the optics of the camera system.
Combining HoloLens with Instant-NeRFs: Advanced Real-Time 3D Mobile Mapping
The HoloLens is connected via Wifi to a high-performance PC that is responsible for the training and 3D reconstruction.
DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
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.
Corrosion Detection for Industrial Objects: From Multi-Sensor System to 5D Feature Space
Corrosion is a form of damage that often appears on the surface of metal-made objects used in industrial applications.
Subpixel-Precise Tracking of Rigid Objects in Real-time
We present a novel object tracking scheme that can track rigid objects in real time.
MVTec D2S: Densely Segmented Supermarket Dataset
The dataset covers several challenges highly relevant in the field, such as a limited amount of training data and a high diversity in the test and validation sets.
