Big Bird: A global dataset of birds in drone imagery annotated to species level

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Authors: Joshua P. Wilson, Richard Fuller, Roxane Francis, Dominik Marchowski, Christian Pfeifer, Alejandro Corregidor Castro, César Luque Fernández, John McEvoy, José Hernán Sarasola, C. Oosthuizen, Jarrod C. Hodgson, Sophie Rawson
+2 more Nicola J. Sockhill, Samantha Wong-Topp
Cited by: 1

Abstract

Big Bird is a globally diverse dataset of images to support the development of computer vision tools for detecting and identifying birds in drone survey imagery. The dataset contains 23,865 images spanning broad biological, digital, and environmental contexts, including over 100 species of birds, 21 different camera systems, and all seven continents. Birds in a subset of 4,824 images are annotated with bounding boxes and biological attributes, including species, posture category, age category, and sex. This subset includes 49,990 bird annotations from 101 species. The dataset is intended to facilitate more efficient monitoring methods to inform effective conservation.

Publication details

Journal / source
The University of Queensland
Publication date
18 January 2026
Document type
Dataset