Machine Learning Competition on an Outdoor Driving Dataset (TAS500v1.1) with a submission deadline on August 15, 2021. The best results are presented as part of the SUUE workshop @ DAGM GCPR 2021 on September 28, 2021 in Bonn, Germany.

Important Dates ==================================================================== * August 15, 2021 – Challenge Deadline * September 28, 2021 – Workshop Presentation Date Overview

====================================================================

The vast majority of research in scene understanding is applied in urban and structured environments. Unfortunately, these methods often fail when used in unstructured environments with challenging lighting conditions and many natural structures in the scene. We therefore invite you to participate in the Outdoor Semantic Segmentation Challenge and give you the opportunity to benchmark your semantic segmentation algorithms on a novel dataset of finely-grained image annotations of real world outdoor driving scenes.

The challenge uses the TAS500 dataset, which consists of over 500 annotated images of different outdoor environments. The dataset applies a fine-grained vegetation and road surface annotation policy. The segmented scenes are of interest for applications in forestry robotics or autonomous driving in unstructured environments. The challenge is part of the 1st Workshop on Scene Understanding in Unstructured Evironments (SUUE 2021) and is organized in conjunction with the DAGM GCPR 2021. The results on the test set will be published on the public leaderboard on Codalab. The participants with the best submissions will be invited to present their results at the SUUE workshop on September 28, 2021.

The workshop presentation can also be pre-recorded or done remotely. We therefore invite the international research community to participate in the competition.

Competition Organizers

====================================================================

Peter Mortimer (Bundeswehr University Munich)

====================================================================

For any additional information feel free to contact us at suueworkshop@googlegroups.com