Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos

Abstract The current biodiversity loss crisis makes animal monitoring a relevant field of study. In light of this, data collected through monitoring can provide essential insights, and information for decision-making aimed at preserving global biodiversity. Despite the importance of such data, there...

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Main Authors: Javier Rodriguez-Juan, David Ortiz-Perez, Manuel Benavent-Lledo, David Mulero-Pérez, Pablo Ruiz-Ponce, Adrian Orihuela-Torres, Jose Garcia-Rodriguez, Esther Sebastián-González
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05516-5
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author Javier Rodriguez-Juan
David Ortiz-Perez
Manuel Benavent-Lledo
David Mulero-Pérez
Pablo Ruiz-Ponce
Adrian Orihuela-Torres
Jose Garcia-Rodriguez
Esther Sebastián-González
author_facet Javier Rodriguez-Juan
David Ortiz-Perez
Manuel Benavent-Lledo
David Mulero-Pérez
Pablo Ruiz-Ponce
Adrian Orihuela-Torres
Jose Garcia-Rodriguez
Esther Sebastián-González
author_sort Javier Rodriguez-Juan
collection DOAJ
description Abstract The current biodiversity loss crisis makes animal monitoring a relevant field of study. In light of this, data collected through monitoring can provide essential insights, and information for decision-making aimed at preserving global biodiversity. Despite the importance of such data, there is a notable scarcity of datasets featuring videos of birds, and none of the existing datasets offer detailed annotations of bird behaviors in video format. In response to this gap, our study introduces the first fine-grained video dataset specifically designed for bird behavior detection and species classification. This dataset addresses the need for comprehensive bird video datasets and provides detailed data on bird actions, facilitating the development of deep learning models to recognize these, similar to the advancements made in human action recognition. The proposed dataset comprises 178 videos recorded in Spanish wetlands, capturing 13 different bird species performing 7 distinct behavior classes. In addition, we also present baseline results using state of the art models on two tasks: bird behavior recognition and species classification.
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institution Kabale University
issn 2052-4463
language English
publishDate 2025-07-01
publisher Nature Portfolio
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series Scientific Data
spelling doaj-art-36ad4d17538d44eeb08ccc7f496299c32025-08-20T04:01:47ZengNature PortfolioScientific Data2052-44632025-07-0112111310.1038/s41597-025-05516-5Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in VideosJavier Rodriguez-Juan0David Ortiz-Perez1Manuel Benavent-Lledo2David Mulero-Pérez3Pablo Ruiz-Ponce4Adrian Orihuela-Torres5Jose Garcia-Rodriguez6Esther Sebastián-González7Department of Computer Technology, University of AlicanteDepartment of Computer Technology, University of AlicanteDepartment of Computer Technology, University of AlicanteDepartment of Computer Technology, University of AlicanteDepartment of Computer Technology, University of AlicanteDepartment of Ecology, University of AlicanteDepartment of Computer Technology, University of AlicanteDepartment of Ecology, University of AlicanteAbstract The current biodiversity loss crisis makes animal monitoring a relevant field of study. In light of this, data collected through monitoring can provide essential insights, and information for decision-making aimed at preserving global biodiversity. Despite the importance of such data, there is a notable scarcity of datasets featuring videos of birds, and none of the existing datasets offer detailed annotations of bird behaviors in video format. In response to this gap, our study introduces the first fine-grained video dataset specifically designed for bird behavior detection and species classification. This dataset addresses the need for comprehensive bird video datasets and provides detailed data on bird actions, facilitating the development of deep learning models to recognize these, similar to the advancements made in human action recognition. The proposed dataset comprises 178 videos recorded in Spanish wetlands, capturing 13 different bird species performing 7 distinct behavior classes. In addition, we also present baseline results using state of the art models on two tasks: bird behavior recognition and species classification.https://doi.org/10.1038/s41597-025-05516-5
spellingShingle Javier Rodriguez-Juan
David Ortiz-Perez
Manuel Benavent-Lledo
David Mulero-Pérez
Pablo Ruiz-Ponce
Adrian Orihuela-Torres
Jose Garcia-Rodriguez
Esther Sebastián-González
Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
Scientific Data
title Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
title_full Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
title_fullStr Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
title_full_unstemmed Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
title_short Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
title_sort visual wetlandbirds dataset bird species identification and behavior recognition in videos
url https://doi.org/10.1038/s41597-025-05516-5
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