Overview & Objective

Driving conditions in India are highly unstructured and diverse, with interesting behaviors of traffic participants, compared to the rest of the world. These driving conditions pose unique challenges that are yet unsolved, for research in artificial intelligence (AI) and machine learning (ML) systems, and hence offer immense opportunities for possible technical innovations in AI/ML systems for better road safety.

India Driving Dataset (IDD) is the world’s first dataset of unstructured driving scenarios. This is an open dataset, available for anyone across the world, for research. IDD was released at the first AutoNUE workshop in the European Conference on Computer Vision (ECCV) 2018 with 50,000 images of ground truth annotation. In the second AutoNUE workshop at the International Conference on Computer Vision ( ICCV) 2019, IDD is expanded to be a multi-modal dataset with more data from stereo camera, LIDAR, and GPS from diverse road conditions.

As part of the NCVPRIPG 2019, we are launching a data challenge:

• Semantic segmentation on IDD Lite Dataset

This challenge is open to students in Indian universities and colleges. The challenge will use IDD-Lite, a dataset that is small and compact to fit on any personal computer and so will not huge-compute infrastructure. IDD-Lite is less than 50MB is size, contains 7 classes (compared to 30 in IDD). The dataset and the evaluation code is already available for participants. An automated leaderboard will be made available on 25-November-2019. We will also be releasing a sample code which gives a baseline accuracy, for the challenge.

Prizes and Travel Grants

Intel is sponsoring the prizes to students - cash prizes to leading entries (or teams), and non-cash prizes as travel grants or conference registration to limited number of select participants in the data challenge.

Directions for Participation

1. Register here, for recieving updates about the competition.
2. Register an account at the IDD website: http://idd.insaan.iiit.ac.in/, if you do not have one.
3. While registering make sure you choose event option to be "NCVPRIPG, IDD Challenge"
4. If you had registered previously at http://idd.insaan.iiit.ac.in/, you will need to go to your profile and change the event option.
5. After logging in to IDD website, download the IDD Lite dataset (http://idd.insaan.iiit.ac.in/dataset/download/)
6. Segmentations masks have all been already generated for IDD Lite in the download.
7. Once you have built a model, and have the predictions of the model in any of the split (train, val), you can evaluate the metric as directed here: https://github.com/AutoNUE/public-code#evaluation. Use the following command for segmentation evaluation:
   python evaluate/idd_lite_evaluate_mIoU.py --gts $GT --preds $PRED --num-workers $C
   Your predictions is a png image, which has the size of 256x128. Each pixel of this image contains the label as level1Ids (see labels code) of the corresponding image (resized to 256x128). The evaluation code above resizes both your prediction and ground truth png files to 256x128, in case they are not of that size.
8. Finally you can upload the predictions for the test split, to be evaluated for the leaderboard here: http://idd.insaan.iiit.ac.in/evaluation/submission/submit/

Program

Date: 22 December, 2019 (Sunday) Venue: NCVPRIPG Main Conference Venue

Important Dates

• IDD Lite dataset (including image/annotation pairs of train, valid splits and images of test split) and the evaluation code is available
• Automated Leaderboard is open here: http://idd.insaan.iiit.ac.in/evaluation/ncv19-leader-board/
• Submissions Closes on 17th December, 2019.
• Winners announced on 18th December, 2019.
• Prize Distribution at NCVPRIPG 2019 during 22-24th December, 2019.

Venue

KLE Technological University
B. V. Bhoomaraddi Campus Vidyanagar, Hubli – 580 031 (INDIA)
Click on the below link
https://goo.gl/maps/k91s6E8PTJC2