[visionlist] CFP: CVPR’21 ActivityNet Challenge - ActEV SDL Unknown Facility (UF) task

[Godil, Afzal A. (Fed)]

Call for Participation: CVPR’21 ActivityNet Challenge Guest Task: ActEV SDL Unknown Facility (UF) Challenge


The ActEV SDL Unknown Facility (UF) challenge is a guest task under the CVPR’21 ActivityNet Challenge (http://activity-net.org/challenges/2021/).  The challenge participants are invited to submit their runnable activity detection system for Known Activities using an ActEV Command Line Interface (CLI) submission on the Unknown Facility EO video dataset.  Based on the UF CLI submission deadline of May 07, 2021, we will invite the top two teams to give oral presentations at the CVPR’21 ActivityNet workshop.


ActEV SDL UF website: https://actev.nist.gov/sdl

CVPR’21 ActivityNet Challenge: http://activity-net.org/challenges/2021/

If you have any question about the SDL UF challenge, please email actev-nist at nist.gov


Who


NIST invites all organizations, particularly universities and corporations, to submit their technologies to ActEV SDL UF.  The evaluation is open worldwide. Participation is free. NIST does not provide funds to participants.


Schedule

  *   February 10, 2021: CVPR’21 ActivityNet ActEV SDL UF (with Known Activities) leaderboard opens
  *   May 07, 2021: Deadline for UF CLI submissions to be included in CVPR’21 ActivityNet workshop.

  *   June 01, 2021: Top two teams on the ActEV'21 SDL UF (with Known Activities) leaderboard invited to give oral presentations at the CVPR’21 ActivityNet workshop based on the CLI submission deadline (May 07, 2021).

  *   June 19, 2021: CVPR’21 ActivityNet workshop

Dataset

Training data is from the Multiview Extended Video with Activities (MEVA) dataset [mevadata.org]. The public MEVA dataset includes hundreds of hours of data from the same cameras at the same facility, which can be used for training. If you register for ActEV you can download the MEVA dataset for free; info on how to download the data is on the data tab https://actev.nist.gov/sdl#tab_data]. Expanded annotations are now available<https://gitlab.kitware.com/meva/meva-data-repo/tree/master/annotation/DIVA-phase-2/MEVA/kitware-meva-training> for public MEVA<http://mevadata.org/> KF1 dataset.

Unknown Facility Sequestered Test dataset is a large collection of videos exclusively in the EO spectrum.

Please contact us if you need any more information or have any question.

Best wishes,

-Afzal for actev-nist at nist.gov

Afzal Godil
Information Technology Laboratory
National Institute of Standards and Technology
godil at nist.gov

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