3.5k citations · 6k across the 59 of their papers we have counts for
13 papers · 1 filter
The Hidden Uncertainty in a Neural Networks Activations
Janis Postels, Hermann Blum, Yannick Strümpler +4
The distribution of a neural network's latent representations has been successfully used to detect out-of-distribution (OOD) data. This work investigates whether this distribution…
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
Le Chen, Yunke Ao, Florian Tschopp +5
Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of…
Out-of-Distribution Detection for Automotive Perception
Julia Nitsch, Masha Itkina, Ransalu Senanayake +5
Neural networks (NNs) are widely used for object classification in autonomous driving. However, NNs can fail on input data not well represented by the training dataset, known as ou…
Freetures: Localization in Signed Distance Function Maps
Alexander Millane, Helen Oleynikova, Christian Lanegger +5
Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps. Existing techniques for ge…
Empty Cities: a Dynamic-Object-Invariant Space for Visual SLAM
Berta Bescos, Cesar Cadena, Jose Neira
In this paper we present a data-driven approach to obtain the static image of a scene, eliminating dynamic objects that might have been present at the time of traversing the scene…
A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments under Severe Odometry Drift
Lukas Schmid, Victor Reijgwart, Lionel Ott +3
Exploration is a fundamental problem in robot autonomy. A major limitation, however, is that during exploration robots oftentimes have to rely on on-board systems alone for state e…