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Fine-Grained Image Recognition datasets
archive 2025-07-28
12 datasets carry the task tag "Fine-Grained Image Recognition" (the task itself: Fine-Grained Image Recognition), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Fine-Grained Image Recognition datasets 1–12 of 12
The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task.
2,235 papers · 47 benchmarks
Omni-Realm Benchmark (OmniBenchmark) is a diverse (21 semantic realm-wise datasets) and concise (realm-wise datasets have no concepts overlapping) benchmark for evaluating pre-trained model generalization across semantic…
29 papers · 1 benchmark
OVEN (Open-domain Visual Entity Recognition)
In this project, we formally present the task of Open-domain Visual Entity recognitioN (OVEN), where a model need to link an image onto a Wikipedia entity with respect to a text query.
19 papers · 1 benchmark
WebFG-496 is a dataset for fine-grained recognition that contains 200 subcategories of the "Bird" (Web-bird), 100 subcategories of the Aircraft" (Web-aircraft), and 196 subcategories of the "Car" (Web-car).
7 papers · 0 benchmarks
CUB-GHA (CUB Gaze-based Human Attention)
CUB-GHA is a dataset for fine-grained classification with human attention annotations.
4 papers · 0 benchmarks
Goldfinch is a dataset for fine-grained recognition challenges.
3 papers · 0 benchmarks
The DAPlankton dataset consists of over 110k expert-labeled plankton images.
2 papers · 0 benchmarks
Introduced originally by Xiaohan Yu, Yang Zhao, Yongsheng Gao, Xiaohui Yuan, Shengwu Xiong (2021).
2 papers · 0 benchmarks
CNFOOD-241 Contains a dataset of 241 Chinese dishes with 191,811 images.
1 paper · 1 benchmark
This dataset concentrates on the activities of the crowd for a fine-grained image classification task, named as Crowd Activity dataset, as automatically understanding crowd activity is meaningful for social security.
1 paper · 0 benchmarks
WikiChurches is a dataset for architectural style classification, consisting of 9,485 images of church buildings.
1 paper · 0 benchmarks
fruit-SALAD is a synthetic image dataset with 10,000 generated images of fruit depictions.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.