SynPeDS: A Synthetic Dataset for Pedestrian Detection in Urban Traffic Scenes

Thomas Stauner, Frédérik Blank, Michael Fürst, Johannes Günther 0001, Korbinian Hagn, Philipp Heidenreich, Markus Huber, Bastian Knerr, Thomas Schulik, Karl-Ferdinand Leiß. SynPeDS: A Synthetic Dataset for Pedestrian Detection in Urban Traffic Scenes. In Björn Brücher, Christoph Krauß, Mario Fritz, Hans-Joachim Hof, Oliver Wasenmüller, editors, Computer Science in Cars Symposium, CSCS 2022, Ingolstadt, Germany, 8 December 2022. ACM, 2022. [doi]

@inproceedings{StaunerBF0HHHKS22,
  title = {SynPeDS: A Synthetic Dataset for Pedestrian Detection in Urban Traffic Scenes},
  author = {Thomas Stauner and Frédérik Blank and Michael Fürst and Johannes Günther 0001 and Korbinian Hagn and Philipp Heidenreich and Markus Huber and Bastian Knerr and Thomas Schulik and Karl-Ferdinand Leiß},
  year = {2022},
  doi = {10.1145/3568160.3570230},
  url = {https://doi.org/10.1145/3568160.3570230},
  researchr = {https://researchr.org/publication/StaunerBF0HHHKS22},
  cites = {0},
  citedby = {0},
  booktitle = {Computer Science in Cars Symposium, CSCS 2022, Ingolstadt, Germany, 8 December 2022},
  editor = {Björn Brücher and Christoph Krauß and Mario Fritz and Hans-Joachim Hof and Oliver Wasenmüller},
  publisher = {ACM},
  isbn = {978-1-4503-9786-5},
}