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Fake Image Detection datasets

archive 2025-07-28

4 datasets carry the task tag "Fake Image Detection" (the task itself: Fake Image Detection), ordered by the archive's paper count. Page 1 of 1: 4 shown of 4. 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

Fake Image Detection datasets 1–4 of 4

Forgery Diversity: DF40 comprises 40 distinct deepfake techniques (both representive and SOTA methods are included), facilitating the detection of nowadays' SOTA deepfakes and AIGCs.
11 papers · 0 benchmarks
ArtiFact (Artificial and Factual Image Dataset for Synthetic Image Detection)
The ArtiFact dataset is a large-scale image dataset that aims to include a diverse collection of real and synthetic images from multiple categories, including Human/Human Faces, Animal/Animal Faces, Places, Vehicles, Art, and many other…
7 papers · 0 benchmarks
The TwinSynths dataset is a novel benchmark designed to overcome common limitations found in earlier synthetic image datasets, such as low image quality, inadequate content preservation, and limited class diversity.
1 paper · 0 benchmarks
This dataset is the images of corn seeds considering the top and bottom view independently (two images for one corn seed: top and bottom).
0 papers · 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.