73 citations · 102 across the 11 of their papers we have counts for
11 papers
Label-Efficient Point Cloud Segmentation with Active Learning
Johannes Meyer, Jasper Hoffmann, Felix Schulz +5
Semantic segmentation of 3D point cloud data often comes with high annotation costs. Active learning automates the process of selecting which data to annotate, reducing the total a…
uPLAM: Robust Panoptic Localization and Mapping Leveraging Perception Uncertainties
Kshitij Sirohi, Daniel Büscher, Wolfram Burgard
The availability of a robust map-based localization system is essential for the operation of many autonomously navigating vehicles. Since uncertainty is an inevitable part of perce…
A Smart Robotic System for Industrial Plant Supervision
D. Adriana Gómez-Rosal, Max Bergau, Georg K. J. Fischer +10
In today's chemical plants, human field operators perform frequent integrity checks to guarantee high safety standards, and thus are possibly the first to encounter dangerous opera…
Uncertainty-aware LiDAR Panoptic Segmentation
Kshitij Sirohi, Sajad Marvi, Daniel Büscher +1
Modern autonomous systems often rely on LiDAR scanners, in particular for autonomous driving scenarios. In this context, reliable scene understanding is indispensable. Current lear…
Uncertainty-aware Panoptic Segmentation
Kshitij Sirohi, Sajad Marvi, Daniel Büscher +1
Reliable scene understanding is indispensable for modern autonomous systems. Current learning-based methods typically try to maximize their performance based on segmentation metric…
Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation
Kürsat Petek, Kshitij Sirohi, Daniel Büscher +1
Robust localization in dense urban scenarios using a low-cost sensor setup and sparse HD maps is highly relevant for the current advances in autonomous driving, but remains a chall…