Welcome to the Vision for Intelligent Vehicles and Applications (VIVA) Challenge!

Our research considers issues in sensing, analysis, modeling, and prediction of parameters associated with drivers, occupants, vehicle dynamics and vehicle surroundings as well as transportation infrastructures. As a benefit to the research community, we are putting together a set of tasks for benchmarking techniques under challenging naturalistic driving settings.

The site currently supports tasks for hands, traffic signs & traffic lights, but will be updated in the near future for additional tasks related to intelligent vehicles.


News:

  • 3/13/2016: Added development kit for training and evaluation on VIVA-Hands detection.
  • 2/17/2016: CALL FOR PARTICIPATION in the VIVA Challenge 2016 at IEEE Intelligent Vehicles (IV) Symposium! Requesting participants to submit their results by June 18th to be considered for awards at the IV workshop.
  • 2/17/2016: The 2nd Workshop on Observing and Understanding Hands in Action will be held with CVPR 2016. We welcome challenge submissions up until the workshop date. Winners and awards will be given at CVPR.
  • 12/17/2015: Traffic Lights datasets is now online.
  • 6/28/2015: VIVA Workshop at IV – Thanks for participating!
  • 6/12/2015: Congratulations to VIVA-Hands gesture challenge winners: Hand Gesture Recognition with 3D Convolutional Neural NetworksP. Molchanov, S. Gupta, K. Kim, and J. Kautz (NVIDIA).
  • 3/5/2015: We are co-organizing a workshop on observing and understanding hands in action at CVPR 2015.
  • 02/01/2015: Hands and traffic signs datasets are online.

 


 

We would like to acknowledge the contribution of the LISA team in the data collection and annotation process, in particular Rakesh Nattoji Rajaram, Nikhil Das, and Kevan Yuen for helpful discussions, help with constructing the challenge, and website design.

 

Notice for using the VIVA datasets:

UC Copyright Notice These datasets are Copyright © 2014 The Regents of the University of California. All Rights Reserved. Permission to copy, modify, and distribute these datasets and its documentation for educational, research and non-profit purposes, without fee, and without a written agreement is hereby granted, provided that the above copyright notice, this paragraph and the following three paragraphs appear in all copies. Permission to make commercial use of these datasets may be obtained by contacting: Technology Transfer Office 9500 Gilman Drive, Mail Code 0910 University of California La Jolla, CA 92093-0910 (858) 534-5815 invent@ucsd.edu This datasets and documentation are copyrighted by The Regents of the University of California. The datasets and documentation are supplied “as is”, without any accompanying services from The Regents. The Regents does not warrant that the operation of the program will be uninterrupted or error-free. The end-user understands that the program was developed for research purposes and is advised not to rely exclusively on the program for any reason.

IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THESE DATASETS AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATASETS PROVIDED HEREUNDER IS ON AN “AS IS” BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.