Zenseact open dataset: A large-scale and diverse multimodal dataset for autonomous driving M Alibeigi, W Ljungbergh, A Tonderski, G Hess, A Lilja, C Lindström, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 60 | 2023 |
Localization is all you evaluate: Data leakage in online mapping datasets and how to fix it A Lilja, J Fu, E Stenborg, L Hammarstrand Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 10 | 2024 |
Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gap C Lindström, G Hess, A Lilja, M Fatemi, L Hammarstrand, C Petersson, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 6 | 2024 |
Multi-object tracking using either end-to-end deep learning or PMBM filtering E Bohnsack, A Lilja | 5 | 2019 |
Exploring Semi-Supervised Learning for Online Mapping A Lilja, E Wallin, J Fu, L Hammarstrand arXiv preprint arXiv:2410.10279, 2024 | | 2024 |
Image segmentation and convolutional neural networks as tools for indoor scene understanding A Liberda, A Lilja, B Langborn, J Lindström, Kahl | | 2016 |
Mastering AchtungDieKurve with Deep Q-Learning using OpenAI Gym E Bohnsack, A Lilja | | |