While several datasets for autonomous navigation have become available in recent years, they have tended to focus on structured driving environments. This usually corresponds to well-delineated infrastructure such as lanes, a small number of well-defined categories for traffic participants, low variation in object or background appearance and strong adherence to traffic rules. We propose a novel dataset for road scene understanding in unstructured environments where the above assumptions are largely not satisfied. It consists of 10,000 images, finely annotated with 34 classes collected from 182 drive sequences on Indian roads. The label set is expanded in comparison to popular benchmarks such as Cityscapes, to account for new classes.

Register and Download

Please click here for registering for the competition and obtaining the dataset.

Challenge

  • Challenge Opens:July 1, 2018
  • Challenge Submission: August 25, 12 Midnight PDT, 2018

Awards

Intel is sponsoring the following awards for the winners of the Challenge:
  • Semantic Segmentation: 1000 USD for the best performing team.
  • Instance Segmentation: 1000 USD for the best performing team.
For qualifying for the award, we also require the team to perform better than the baseline performance. The final baselines will be released at least 2 weeks before the deadline, along with images of the test set.

Organizers

iiit-H


intel
ucsd
uutah