The challenge will be on pollutant prediction in Grenoble area, in collaboration with ATMO Auvergne-Rhône Alpes.
See https://competitions.codalab.org/competitions/20430?secret_key=9c39a737-0965-4120-89a4-d8b6cc08eddb
See https://competitions.codalab.org/competitions/20430?secret_key=9c39a737-0965-4120-89a4-d8b6cc08eddb.
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The presentation and report should contain a description of the different approaches you tried, even if some of them were discarded because of unsatisfactory results. The report has to be exhaustive on that point, while the presentation may focus on 2 or 3 of them. There should be associated values and comparisons of the metrics, and on execution times. Try to analyse the shortcomings of the methods, explain how you gradually overcame them, and what could be further improved in your final proposal.
The oral presentation should last from 18 to 20 minutes and will be followed by questions. You may not spend more than one slide / 1 min 30 on the problem description and data, since these are common to every team.
The report should be from 4 to 10 pages long. You have to deliver it just before the presentations.
The challenge will be on audio-visual speaker diarization.
The data can be downloaded from https://github.com/Stephlat/dataChallengePerception. This page also contains details about the data and basic scripts for data visualization.
The presentation and report should contain a description of the different approaches you tried, even if some of them were discarded because of unsatisfactory results. The report has to be exhaustive on that point, while the presentation may focus on 2 or 3 of them. There should be associated values and comparisons of the metrics, and on execution times. Try to analyse the shortcomings of the methods, explain how you gradually overcame them, and what could be further improved in your final proposal.
The oral presentation should last from 18 to 20 minutes and will be followed by questions. Presentations will start at 1:30 PM (or maybe 2PM, depending on participant's constraints). You may not spend more than one slide / 1 min 30 on the problem description and data, since these are common to every team.
The report should be from 4 to 10 pages long. You have to deliver it just before the presentations.
Please have a close-to-final version of both reports and slides on Thursday evening.
The link to the test data is available on https://github.com/Stephlat/dataChallengePerception
You have to submit your predictions before 11:00 AM by sending a .zip archive containing 4 folders named Scenario03-MeetingRoom04 Scenario05-04 Scenario01-03 and Scenario05-03. In each of these, you must place your detection.txt files (but no .avi files).
Join to your archive the exact python code (whole set of scripts) that has been used to produce the detection.txt files.
Send your email Jean-Baptiste.Durand@univ-grenoble-alpes.fr, guillaume.delorme@inria.fr and stephane.lathuiliere@inria.fr.
The final score used to ranked teams is the mean MOTSA on the 4 videos, weighted by video lengths.
Send your report and presentation (PDF format only) before 1:30 PM at Jean-Baptiste.Durand@univ-grenoble-alpes.fr, guillaume.delorme@inria.fr, stephane.lathuiliere@inria.fr, li.liu@gipsa-lab.grenoble-inp.fr, olivier.michel@gipsa-lab.grenoble-inp.fr, Massih-Reza.Amini@univ-grenoble-alpes.fr and Radu.Horaud@inria.fr.