Johan Vertens

According to our database, Johan Vertens authored at least 15 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multimodal perception and mapping for autonomous vehicles.

Johan Vertens

PhD thesis, 2024

2023

Improving Deep Dynamics Models for Autonomous Vehicles with Multimodal Latent Mapping of Surfaces.

Johan Vertens, Nicolai Dorka, Tim Welschehold, Michael Thompson, Wolfram Burgard

IROS, 2023

2022

USegScene: Unsupervised Learning of Depth, Optical Flow and Ego-Motion with Semantic Guidance and Coupled Networks.

Johan Vertens, Wolfram Burgard

CoRR, 2022

Realistic Real-Time Simulation of RGB and Depth Sensors for Dynamic Scenarios using Augmented Image Based Rendering.

Johan Vertens, Wolfram Burgard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Long-term vehicle localization in urban environments based on pole landmarks extracted from 3-D lidar scans.

Alexander Schaefer, Daniel Büscher, Johan Vertens, Lukas Luft, Wolfram Burgard

Robotics Auton. Syst., 2021

Lane Graph Estimation for Scene Understanding in Urban Driving.

Jannik Zürn, Johan Vertens, Wolfram Burgard

IEEE Robotics Autom. Lett., 2021

2020

HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images.

Johan Vertens, Jannik Zürn, Wolfram Burgard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning Object Placements For Relational Instructions by Hallucinating Scene Representations.

Oier Mees, Alp Emek, Johan Vertens, Wolfram Burgard

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

A Maximum Likelihood Approach to Extract Finite Planes from 3-D Laser Scans.

Alexander Schaefer, Johan Vertens, Daniel Büscher, Wolfram Burgard

Proceedings of the International Conference on Robotics and Automation, 2019

Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans.

Alexander Schaefer, Daniel Büscher, Johan Vertens, Lukas Luft, Wolfram Burgard

Proceedings of the 2019 European Conference on Mobile Robots, 2019

2017

From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields.

Florian Kraemer, Alexander Schaefer, Andreas Eitel, Johan Vertens, Wolfram Burgard

CoRR, 2017

Perspectives on Deep Multimodel Robot Learning.

Wolfram Burgard, Abhinav Valada, Noha Radwan, Tayyab Naseer, Jingwei Zhang, Johan Vertens, Oier Mees, Andreas Eitel, Gabriel L. Oliveira

Proceedings of the Robotics Research, The 18th International Symposium, 2017

SMSnet: Semantic motion segmentation using deep convolutional neural networks.

Johan Vertens, Abhinav Valada, Wolfram Burgard

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

AdapNet: Adaptive semantic segmentation in adverse environmental conditions.

Abhinav Valada, Johan Vertens, Ankit Dhall, Wolfram Burgard

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2015

Measuring Respiration and Heart Rate using Two Acceleration Sensors on a Fully Embedded Platform.

Johan Vertens, Fabian Fischer, Christian Heyde, Fabian Hoeflinger, Rui Zhang, Leonhard M. Reindl, Albert Gollhofer

Proceedings of the 3rd International Congress on Sport Sciences Research and Technology Support, 2015