iNaturalist 2021 (iNat-2021) is a large-scale fine-grained species recognition benchmark derived from the iNaturalist community observations and released for the FGVC8 / iNat Challenge (2021). The dataset is designed for large-scale, long-tailed image classification of plants/animals/insects with many visually similar classes. The iNat2021 challenge split contains roughly 10,000 species and ≈2.7 million training images (there is also a "mini" version with 50 images per species, ≈500K images). Images were collected and user-verified via iNaturalist, and the benchmark emphasizes real-world class imbalance and fine-grained discrimination. Common uses: supervised image classification, long-tailed / fine-grained recognition, and semi-supervised variants (e.g., Semi-iNat2021). Sources: FGVC8 iNat Challenge 2021 pages and the visipedia iNat competition repository (inat_comp/2021). Note: the original iNaturalist dataset was introduced in Van Horn et al., CVPR 2018 (arXiv:1707.06642); iNaturalist 2021 is a later challenge release built on the iNaturalist platform rather than a separate peer-reviewed dataset paper.
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