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DeepFake Detection archive 2025-07-28

FakeAVCeleb Benchmark (DeepFake Detection)

13 rows 10 with code listed 3 metrics Dataset page

DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. The goal of deepfake detection is to identify such manipulations and distinguish them from real videos or images.

Description source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Image source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

The archive carries no text for this table; the description above is the archive's text for the task DeepFake Detection. archive 2025-07-28

Over time archive 2025-07-28

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Direction inferred from the metric name, not from the archive: ROC AUC (higher is better), AP (higher is better), Accuracy (%) (higher is better). Points are placed at the row's paper date; 13 of 13 rows carry one.

Results archive 2025-07-28

Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.

Paper Code Ran Syntology Report
1 FACTOR 97.496.8 – Paper Code 2023 linked, not harvested report
2 RealForensics 97.195.3 – Paper Code 2022 0 of 9 ran · 9 unverified report
3 AVAD 94.594.2 – Paper Code 2023 0 of 1 ran · 1 unverified report
4 FTCN 93.192.3 – Paper Code 2021 6 of 6 ran · 0 unverified report
5 LipForensics 91.189.4 – Paper Code 2020 1 of 2 ran · 1 unverified report
6 AD DFD 88.188.8 – Paper – 2021 no code linked report
7 Xception 85.384.8 – Paper Code 2019 4 of 9 ran · 5 unverified report
8 AVBYOL 59.273.9 – Paper Code 2022 0 of 9 ran · 9 unverified report
9 VQGAN 51.855.0 – Paper Code 2020 6 of 6 ran · 0 unverified report
10 AV-Lip-Sync+ 99.29 – Paper – 2023 no code linked report
11 Avtenet 98.57 – Paper – 2023 no code linked report
12 AV-Lip-Sync Model 94 – Paper Code 2022 linked, not harvested report
13 Multimodal Ensemble Model 89 – Paper Code 2022 linked, not harvested report

All 13 rows shown. 13 link to a paper page on this site; 0 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28

Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 7 rows have a graph line, from 6 distinct papers; 4 rows (4 papers) have at least one sample that ran. Counting each paper once: Syntology ran 17 of 33 samples; 16 unverified. Separately, 14 of those 33 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.

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