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Face Anti-Spoofing datasets

archive 2025-07-28

17 datasets carry the task tag "Face Anti-Spoofing" (the task itself: Face Anti-Spoofing), ordered by the archive's paper count. Page 1 of 1: 17 shown of 17. 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

Face Anti-Spoofing datasets 1–17 of 17

The Replay-Attack Database for face spoofing consists of 1300 video clips of photo and video attack attempts to 50 clients, under different lighting conditions.
133 papers · 1 benchmark
The MSU-MFSD dataset contains 280 video recordings of genuine and attack faces.
89 papers · 1 benchmark
CASIA-MFSD is a dataset for face anti-spoofing.
58 papers · 1 benchmark
SiW (Spoofing in the Wild)
SiW provides live and spoof videos from 165 subjects.
51 papers · 1 benchmark
CASIA-FASD is a small face anti-spoofing dataset containing 50 subjects.
42 papers · 0 benchmarks
CelebA-Spoof is a large-scale face anti-spoofing dataset with the following properties: 1.
28 papers · 0 benchmarks
Dataset for face anti-spoofing in terms of both subjects and modalities.
24 papers · 0 benchmarks
The Replay-Mobile Database for face spoofing consists of 1190 video clips of photo and video attack attempts to 40 clients, under different lighting conditions.
18 papers · 0 benchmarks
HiFiMask (CASIA-SURF HiFiMask)
HiFiMask is a large-scale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask).
14 papers · 0 benchmarks
HQ-WMCA (High-Quality Wide Multi-Channel Attack database)
The High-Quality Wide Multi-Channel Attack database (HQ-WMCA) database consists of 2904 short multi-modal video recordings of both bona-fide and presentation attacks.
9 papers · 0 benchmarks
The Oulu-NPU face presentation attack detection database consists of 4950 real access and attack videos.
8 papers · 1 benchmark
A multimodal database for eye blink detection and attention level estimation.
6 papers · 0 benchmarks
MLFP (Multispectral Latex Mask based Video Face Presentation Attack)
The MLFP dataset consists of face presentation attacks captured with seven 3D latex masks and three 2D print attacks.
4 papers · 1 benchmark
CelebA-Spoof is a large-scale face anti-spoofing dataset recently introduced in [53].
3 papers · 1 benchmark
SiW (Spoofing in the Wild) is a face anti-spoofing dataset recently introduced in [29] where images are extracted from short videos captured at high resolution and 30 frames per second.
3 papers · 1 benchmark
SWAX (Sense Wax Attack dataset)
Comprised of real human and wax figure images and videos that endorse the problem of face spoofing detection.
2 papers · 0 benchmarks
SuHiFiMask (Surveillance High-Fidelity Mask)
SuHiFiMask (Surveillance High-Fidelity Mask) extends FAS to real surveillance scenes rather than mimicking low-resolution images and surveillance environments.
2 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.