3.5k citations · 6k across the 59 of their papers we have counts for
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Continual Adaptation of Semantic Segmentation using Complementary 2D-3D Data Representations
Jonas Frey, Hermann Blum, Francesco Milano +2
Semantic segmentation networks are usually pre-trained once and not updated during deployment. As a consequence, misclassifications commonly occur if the distribution of the traini…
NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping
Stefan Lionar, Lukas Schmid, Cesar Cadena +2
We present a novel 3D mapping method leveraging the recent progress in neural implicit representation for 3D reconstruction. Most existing state-of-the-art neural implicit represen…
See Yourself in Others: Attending Multiple Tasks for Own Failure Detection
Boyang Sun, Jiaxu Xing, Hermann Blum +2
Autonomous robots deal with unexpected scenarios in real environments. Given input images, various visual perception tasks can be performed, e.g., semantic segmentation, depth esti…
Superquadric Object Representation for Optimization-based Semantic SLAM
Florian Tschopp, Juan Nieto, Roland Siegwart +1
Introducing semantically meaningful objects to visual Simultaneous Localization And Mapping (SLAM) has the potential to improve both the accuracy and reliability of pose estimates,…
Panoptic Multi-TSDFs: a Flexible Representation for Online Multi-resolution Volumetric Mapping and Long-term Dynamic Scene Consistency
Lukas Schmid, Jeffrey Delmerico, Johannes Schönberger +4
For robotic interaction in environments shared with other agents, access to volumetric and semantic maps of the scene is crucial. However, such environments are inevitably subject…
Self-Improving Semantic Perception for Indoor Localisation
Hermann Blum, Francesco Milano, René Zurbrügg +3
We propose a novel robotic system that can improve its perception during deployment. Contrary to the established approach of learning semantics from large datasets and deploying fi…