Georg Hess

According to our database, Georg Hess authored at least 13 papers between 2021 and 2024.

Collaborative distances:

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

2024

LidarCLIP or: How I Learned to Talk to Point Clouds.

Georg Hess, Adam Tonderski, Christoffer Petersson, Kalle Åström, Lennart Svensson

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

NeuRAD: Neural Rendering for Autonomous Driving.

Adam Tonderski, Carl Lindström, Georg Hess, William Ljungbergh, Lennart Svensson, Christoffer Petersson

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gap.

Carl Lindström, Georg Hess, Adam Lilja, Maryam Fatemi, Lars Hammarstrand, Christoffer Petersson, Lennart Svensson

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Deep Learning for Model-Based Multiobject Tracking.

Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Henk Wymeersch, Lennart Svensson

IEEE Trans. Aerosp. Electron. Syst., December, 2023

Transformer-Based Multi-Object Smoothing with Decoupled Data Association and Smoothing.

Juliano Pinto, Georg Hess, Yuxuan Xia, Henk Wymeersch, Lennart Svensson

CoRR, 2023

Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds.

Georg Hess, Johan Jaxing, Elias Svensson, David Hagerman, Christoffer Petersson, Lennart Svensson

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving.

Mina Alibeigi, William Ljungbergh, Adam Tonderski, Georg Hess, Adam Lilja, Carl Lindström, Daria Motorniuk, Junsheng Fu, Jenny Widahl, Christoffer Petersson

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Masked Autoencoders for Self-Supervised Learning on Automotive Point Clouds.

Georg Hess, Johan Jaxing, Elias Svensson, David Hagerman, Christoffer Petersson, Lennart Svensson

CoRR, 2022

Can Deep Learning be Applied to Model-Based Multi-Object Tracking?

Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Henk Wymeersch, Lennart Svensson

CoRR, 2022

Object Detection as Probabilistic Set Prediction.

Georg Hess, Christoffer Petersson, Lennart Svensson

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Deep Deterministic Path Following.

Georg Hess, William Ljungbergh

CoRR, 2021

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning.

Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Lennart Svensson, Henk Wymeersch

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

Trajectory Generation for Mobile Robots in a Dynamic Environment using Nonlinear Model Predictive Control.

Jonas Berlin, Georg Hess, Anton Karlsson, William Ljungbergh, Ze Zhang, Knut Åkesson, Per-Lage Götvall

Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021