English

Automated Scene Flow Data Generation for Training and Verification

Computer Vision and Pattern Recognition 2018-09-03 v2

Abstract

Scene flow describes the 3D position as well as the 3D motion of each pixel in an image. Such algorithms are the basis for many state-of-the-art autonomous or automated driving functions. For verification and training large amounts of ground truth data is required, which is not available for real data. In this paper, we demonstrate a technology to create synthetic data with dense and precise scene flow ground truth.

Keywords

Cite

@article{arxiv.1808.10232,
  title  = {Automated Scene Flow Data Generation for Training and Verification},
  author = {Oliver Wasenmüller and René Schuster and Didier Stricker and Karl Leiss and Jürger Pfister and Oleksandra Ganus and Julian Tatsch and Artem Savkin and Nikolas Brasch},
  journal= {arXiv preprint arXiv:1808.10232},
  year   = {2018}
}
R2 v1 2026-06-23T03:49:02.680Z