The 2nd workshop on Unsupervised Learning for Automated Driving (ULAD) was held at the IEEE Intelligent Vehicles Symposium 2020 on October 23, 2020. Due to the travel restrictions, the workshop was held fully virtually. 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.

This year’s keynote speakers include:

  • Anima Anandkumar (Professor at Caltech, director of ML at NVIDIA)
  • Zsolt Kira (Assistant professor at Georgia Tech)
  • Tudor Achim (CTO at, Stanford)
  • Sertac Karaman (Associate Professor at MIT)

For videos and slides, see the ULAD 2020 website.
The workshop was organized by Julian Kooij (Intelligent Vehicles Group, TU Delft) and Fabian Flohr (Daimler AG, Germany).