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arXiv · 2406.09211

WildlifeReID-10k: Wildlife re-identification dataset with 10k individual animals

Lukáš Adam·Vojtěch Čermák·Kostas Papafitsoros·Lukas Picek
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Abstract

This paper introduces WildlifeReID-10k, a new large-scale re-identification benchmark with more than 10k animal identities of around 33 species across more than 140k images, re-sampled from 37 existing datasets. WildlifeReID-10k covers diverse animal species and poses significant challenges for SoTA methods, ensuring fair and robust evaluation through its time-aware and similarity-aware split protocol. The latter is designed to address the common issue of training-to-test data leakage caused by visually similar images appearing in both training and test sets. The WildlifeReID-10k dataset and benchmark are publicly available on Kaggle, along with strong baselines for both closed-set and open-set evaluation, enabling fair, transparent, and standardized evaluation of not just multi-species animal re-identification models.

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Lukáš Adam, Vojtěch Čermák, Kostas Papafitsoros, Lukas Picek. 2024-06-13. WildlifeReID-10k: Wildlife re-identification dataset with 10k individual animals. https://arxiv.org/abs/2406.09211

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