Overview of AnimalCLEF 2025: Recognizing Individual Animals in Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F25%3A43976594" target="_blank" >RIV/49777513:23220/25:43976594 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/49777513:23520/25:43976594

Výsledek na webu

<a href="https://ceur-ws.org/Vol-4038/paper_231.pdf" target="_blank" >https://ceur-ws.org/Vol-4038/paper_231.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Overview of AnimalCLEF 2025: Recognizing Individual Animals in Images

Popis výsledku v původním jazyce

The first edition of the individual animal identification challenge, AnimalCLEF 2025, organized within LifeCLEF,advances the field of animal re-identification using computer vision and machine learning. Building on theWildlifeReID-10k dataset and incorporating new data, AnimalCLEF 2025 challenges participants to recognizeindividual animals from images for three species: lynxes, salamanders and sea turtles. The mix of species withdifferent image capture conditions attempts to make the submitted prediction models generalizable to unseenspecies. The competition attracted 270 participants across 230 teams, with 136 outperforming the provided baselinebased on MegaDescriptor. This overview paper provides (i) a comprehensive description of the challenge andprovided baseline method, (ii) detailed characteristics of the dataset and task specifications, (iii) an examinationof the methods employed by contestants, and (iv) a discussion of the competition outcomes. The results highlightincremental advancements in animal re-identification, showcasing innovative approaches and techniques thatpush the limits of previous work.

Název v anglickém jazyce

Overview of AnimalCLEF 2025: Recognizing Individual Animals in Images

Popis výsledku anglicky

The first edition of the individual animal identification challenge, AnimalCLEF 2025, organized within LifeCLEF,advances the field of animal re-identification using computer vision and machine learning. Building on theWildlifeReID-10k dataset and incorporating new data, AnimalCLEF 2025 challenges participants to recognizeindividual animals from images for three species: lynxes, salamanders and sea turtles. The mix of species withdifferent image capture conditions attempts to make the submitted prediction models generalizable to unseenspecies. The competition attracted 270 participants across 230 teams, with 136 outperforming the provided baselinebased on MegaDescriptor. This overview paper provides (i) a comprehensive description of the challenge andprovided baseline method, (ii) detailed characteristics of the dataset and task specifications, (iii) an examinationof the methods employed by contestants, and (iv) a discussion of the competition outcomes. The results highlightincremental advancements in animal re-identification, showcasing innovative approaches and techniques thatpush the limits of previous work.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

CEUR Workshop Proceedings

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

11

Strana od-do

2898-2908

Název nakladatele

CEUR-WS

Místo vydání

neuveden

Místo konání akce

Madrid

Datum konání akce

9. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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