iNaturalist 2019 (iNat 2019) is a fine-grained species classification dataset and challenge derived from observations on the citizen-science platform iNaturalist. The 2019 FGVC (iNat Challenge 2019) release was organized as part of FGVC6/CVPR 2019 and focuses on large-scale, real-world species recognition with many visually similar categories and a highly imbalanced class distribution. The FGVC6 challenge page reports that the 2019 split contains 1,010 species with a combined training+validation set of 268,243 images (images verified by multiple users on iNaturalist). The dataset is intended for image classification (species identification) and has been widely used as a fine-grained classification benchmark; papers typically report top-1 classification accuracy when evaluating models trained or fine-tuned on this split. The iNaturalist project more broadly (earlier/larger releases) was introduced in the CVPR 2018 paper “The iNaturalist Species Classification and Detection Dataset” (Van Horn et al.), arXiv:1707.06642 / CVPR 2018.
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