Christoffer Petersson

According to our database, Christoffer Petersson authored at least 18 papers between 2021 and 2024.

Collaborative distances:

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

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

CoRR, 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

2023

Geometric deep learning and equivariant neural networks.

Jan E. Gerken, Jimmy Aronsson, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson

Artif. Intell. Rev., December, 2023

NeuRAD: Neural Rendering for Autonomous Driving.

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

CoRR, 2023

HEAL-SWIN: A Vision Transformer On The Sphere.

Oscar Carlsson, Jan E. Gerken, Hampus Linander, Heiner Spieß, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson

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

Raw or Cooked? Object Detection on RAW Images.

William Ljungbergh, Joakim Johnander, Christoffer Petersson, Michael Felsberg

Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

You can have your ensemble and run it too - Deep Ensembles Spread Over Time.

Isak Meding, Alexander Bodin, Adam Tonderski, Joakim Johnander, Christoffer Petersson, Lennart Svensson

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

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml.

Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini, Marcel Roed, Sioni Summers, Thea Aarrestad, Christoffer Petersson, Hampus Linander, Jennifer Ngadiuba, Kelvin Lin, Philip C. Harris

Mach. Learn. Sci. Technol., December, 2022

Towards Explainable Motion Prediction using Heterogeneous Graph Representations.

Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander, Christoffer Petersson, David Fernández Llorca

CoRR, 2022

Towards Trustworthy Multi-Modal Motion Prediction: Evaluation and Interpretability.

Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander, Christoffer Petersson, Miguel Ángel Sotelo, David Fernández Llorca

CoRR, 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

Learning Future Object Prediction with a Spatiotemporal Detection Transformer.

Adam Tonderski, Joakim Johnander, Christoffer Petersson, Kalle Åström

CoRR, 2022

Equivariance versus Augmentation for Spherical Images.

Jan E. Gerken, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson

Proceedings of the International Conference on Machine Learning, 2022

Object Detection as Probabilistic Set Prediction.

Georg Hess, Christoffer Petersson, Lennart Svensson

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Fast convolutional neural networks on FPGAs with hls4ml.

Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang

Mach. Learn. Sci. Technol., 2021

Fast convolutional neural networks on FPGAs with hls4ml.

Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang

CoRR, 2021