Marius Kästingschäfer and Théo Gieruc and Sebastian Bernhard and Dylan Campbell and Eldar Insafutdinov and Eyvaz Najafli and Thomas Brox
Project page | Paper | Data
Models for egocentric 3D and 4D reconstruction, including few-shot interpolation and extrapolation settings, can benefit from having images from exocentric viewpoints as supervision signals. No existing dataset provides the necessary mixture of complex, dynamic, and multi-view data. To facilitate the development of 3D and 4D reconstruction methods in the autonomous driving context, we propose a Synthetic Ego--Exo Dynamic 4D (SEED4D) dataset. We here provide the code with which we generated the data.
Our data generator is build on CARLA and can generator synthetic egocentrical views similar to the camera setup in nuScenes, KITTI360 or Waymo and simultaneously create create exocentrical views. Resulting poses are outputted in a Nerfstudio suitable data format.
We thank the creators of NeRFStudio, and the CARLA simulator for generously open-sourcing their code.
Copyright (C) 2025 co-pace GmbH (subsidiary of Continental AG). All rights reserved. This repository is licensed under the BSD-3-Clause license. See LICENSE for the full license text.
If you find this code useful, please reference in your paper:
@article{seed4d,
title={SEED4D: A Synthetic Ego--Exo Dynamic 4D Data Generator, Driving Dataset and Benchmark},
author={Marius Kästingschäfer and Théo Gieruc and Sebastian Bernhard and Dylan Campbell and Eldar Insafutdinov and Eyvaz Najafli and Thomas Brox},
year={2024},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2412.00730},
journal={arXiv preprint},
volume={arXiv:2412.00730},
}