The 1st workshop on Unsupervised Learning for Automated Driving (ULAD) was held at the IEEE Intelligent Vehicles Symposium 2019 on June 9, 2019 in Paris.
Topic: Unlabelled data is easily collected, increasing traction in IV to explore unsupervised learning, its semi-, weakly-, and self-supervised variants, transfer learning, and inferring probabilistic latent representations. Share novel methodological developments, challenges and solutions for exploiting unlabelled data and reducing the annotation bottleneck.

The keynote speakers include:

  • Adrien Gaidon (Machine Learning Lead at Toyota Research Institute)
  • Antonio M. L√≥pez (Computer Vision Center (CVC), Univ. Autonoma de Barcelona (UAB))
  • Tuan-Hung VU (Research Scientist at Valeo.ai)
  • Rob Weston (Oxford Robotics Institute)

Additionally, we had two oral paper presentations by Karen Leung and Evgeny Kusmenko.

For videos and slides, see the ULAD 2019 website.
The workshop was organized by Julian Kooij (Intelligent Vehicles Group, TU Delft), Fabian Flohr (Daimler AG, Germany) and Christoph Stiller (KIT).