SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic
Kashyap Chitta, Daniel Dauner, and Andreas Geiger
University of Tübingen, Tübingen AI CenterEuropean Conference on Computer Vision (ECCV), 2024
This repo contains SLEDGE, the first generative simulator for vehicle motion planning trained on real-world driving logs. We will be publicly releasing our code for simulation, evaluation, and training (including pre-trained checkpoints).
https://github.com/autonomousvision/sledge/assets/50077664/1c653fda-6e44-4018-ae98-2ab3d0439cad
18 Aug, 2024
: We released v0.1 of the SLEDGE code!01 Jul, 2024
: Our paper was accepted at ECCV 2024 🇮🇹27 Mar, 2024
: We released our paper on arXiv![2024/08/18]
SLEDGE v0.1 release
If you have any questions or suggestions, please feel free to open an issue or contact us (daniel.dauner@uni-tuebingen.de).
If you find SLEDGE useful, please consider giving us a star 🌟 and citing our paper with the following BibTeX entry.
@InProceedings{Chitta2024ECCV,
title = {SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic},
author = {Kashyap Chitta and Daniel Dauner and Andreas Geiger},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2024},
}