2 citations · 2 across the 6 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2024
From One to the Power of Many: Invariance to Multi-LiDAR Perception from Single-Sensor Datasets
Marc Uecker, J. Marius Zöllner
Recently, LiDAR segmentation methods for autonomous vehicles, powered by deep neural networks, have experienced steep growth in performance on classic benchmarks, such as nuScenes…
cs.CV2022★ 2 cited
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception
Marc Uecker, Tobias Fleck, Marcel Pflugfelder +1
LiDAR sensors are an integral part of modern autonomous vehicles as they provide an accurate, high-resolution 3D representation of the vehicle's surroundings. However, it is comput…
cs.CV2020
AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation
David Kügler, Marc Uecker, Arjan Kuijper +1
Despite recent successes, the advances in Deep Learning have not yet been fully translated to Computer Assisted Intervention (CAI) problems such as pose estimation of surgical inst…