Description Task
![Illustration of GeoLifeCLEF dataset](https://raw.githubusercontent.com/maximiliense/GLC/master/images/dataset_illustration.jpg)
The aim of this competition is to predict the localization of plant and animal species.
To do so, 1.6M geo-localized observations from France and the US of 17K species are provided (9K plant species and 8K animal species).
These observations are paired with aerial images and environmental features around them (as illustrated above).
The goal is, for each GPS position in the test set (for which we provide the associated aerial images and environmental features), to return a set of candidate species that should contain the true observed species.
Motivation
Automatic prediction of the list of species most likely to be observed at a given location is useful for many scenarios related to biodiversity management and conservation.
First, this would allow to improve species identification tools - automatic, semi-automatic, or based on traditional field guides - by reducing the list of candidate species observable at a given site.
More generally, it could facilitate biodiversity inventories through the development of location-based recommendation services (e.g. on mobile phones), encourage the involvement of citizen scientist observers, and accelerate the annotation and validation of species observations to produce large, high-quality data sets.
Finally, this could be used for educational purposes through biodiversity discovery applications with features such as contextualized educational pathways.
Context
This competition is held jointly as part of:
the
[LifeCLEF 2022](https://www.imageclef.org/LifeCLEF2022)
lab of the
[CLEF 2022](http://clef2022.clef-initiative.eu)
conference, and of
the
[FGVC9](https://sites.google.com/view/fgvc9)
workshop organized in conjunction with
[CVPR 2022](http://cvpr2022.thecvf.com)
conference.
Being part of scientific research, the participants are encouraged to participate to both event.
In particular, only participants who submitted a working note paper to LifeCLEF (see below) will be part of the officially published ranking used for scientific communication.
FGVC9 at CVPR 2022
This competition is part of the Fine-Grained Visual Categorization
[FGVC9](https://sites.google.com/view/fgvc9)
workshop at the Computer Vision and Pattern Recognition Conference
[CVPR 2022](http://cvpr2022.thecvf.com)
.
A panel will review the top submissions for the competition based on the description of the methods provided.
From this, a subset may be invited to present their results at the workshop.
Attending the workshop is not required to participate in the competition; however, only teams that are attending the workshop will be considered to present their work.
CVPR 2022 will take place in New Orleans, USA, 19-24 June 2022.
PLEASE NOTE: CVPR frequently sells out early, we cannot guarantee CVPR registration after the competition's end.
If you are interested in attending, please plan ahead.
You can see a list of all of the FGVC9 competitions
[here](https://sites.google.com/view/fgvc9/competitions)
.
LifeCLEF 2022
LifeCLEF lab is part of the Conference and Labs of the Evaluation Forum (
[CLEF](http://www.clef-initiative.eu)
).
CLEF consists of independent peer-reviewed workshops on a broad range of challenges in the fields of multilingual and multimodal information access evaluation, and a set of benchmarking activities carried in various labs designed to test different aspects of mono and cross-language Information retrieval systems.
CLEF 2022 will be hosted by the Università di Bologna, Italy, 5-8 September 2022.
More details can be found on the
[CLEF 2022 website](http://clef2022.clef-initiative.eu)
.
To participate to the LifeCLEF lab, participants must register using
[this form](http://clef2022-labs-registration.dei.unipd.it/registrationForm.php)
(and checking "Task 3 - GeoLifeCLEF" of "LifeCLEF" section).
This registration is free of charge and will close on 22 April 2022, however free of charge late registration will still be possible at the end of the competition.
This will allow those participants to submit, at the end of the competition, a working note paper to LifeCLEF which will be peer-reviewed and published in
[CEUR-WS proceedings](http://ceur-ws.org)
.
This paper should provide sufficient information to reproduce the final submitted runs.
Submitting a working note with the full description of the methods used in each run is mandatory.
Any run that could not be reproduced thanks to its description in the working notes might be removed from the official publication of the results.
Working notes are published within CEUR-WS proceedings, resulting in an assignment of an individual DOI (URN) and an indexing by many bibliography systems including DBLP.
According to the CEUR-WS policies, a light review of the working notes will be conducted by LifeCLEF organizing committee to ensure quality.
As an illustration, LifeCLEF 2021 working notes (task overviews and participant working notes) can be found within
[CLEF 2021 CEUR-WS proceedings](http://ceur-ws.org/Vol-2936)
.
Credits
This project has received funding from the French National Research Agency under the Investments for the Future Program, referred to as ANR-16-CONV-0004, and from the European Union’s Horizon 2020 research and innovation program under grant agreement No 863463 (Cos4Cloud project).