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Fake Image Detection research benchmarks – Page 2 · SOTA2 Research

Fake Image Detection

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Synthbuster SD 1.3 (test)

Ours_super-res_3.3

99.9Accuracy

12

Feb 26, 2026

GenImage++ (test)

99.85Flux Score

11

Jun 16, 2026

99.9BA

9

May 27, 2026

Cross-Generator Generalization Trained on ProGAN (test)

100Pro-GAN Detection Rate

9

Feb 26, 2026

96.01AA

9

Feb 26, 2026

95.17AA

9

Feb 26, 2026

95.69AA

9

Feb 26, 2026

98.38AA

9

Feb 26, 2026

98.3AA

9

Feb 26, 2026

98.8AA

9

Feb 26, 2026

98.54AA

9

Feb 26, 2026

98.81AA

9

Feb 26, 2026

98.97AA

9

Feb 26, 2026

three-stage domain continual learning framework

98.38AA

9

Feb 26, 2026

99.57AA Score

9

Feb 26, 2026

99.34AA

9

Feb 26, 2026

three-stage domain continual learning framework

99.06AA

9

Feb 26, 2026

99.99Accuracy

9

Feb 26, 2026

MM-FakeBench Overall

96.3Accuracy

8

May 29, 2026

MM-FakeBench (Fake)

93.2Accuracy

8

May 29, 2026

MM-FakeBench Real

98.2Accuracy

8

May 29, 2026

Cross-Generator Generalization Suite (StyleSwim, WFIR, InstantID, IP-Adapter, Midjourney, SD3, FaceSwap, InSwap, CommunityAI, SocialRF) (test)

93.22StyleSwim Score

8

May 11, 2026

Cross-Generator Aggregate

0.264Avg NLL

8

May 11, 2026

In-the-Wild CommunityAI SocialRF

0.788CommunityAI NLL

8

May 11, 2026

Deepfakes FaceSwap, InSwap

0.016FaceSwap NLL

8

May 11, 2026

Page 2 of 3

Popular datasets

UniversalFakeDetect Synthbuster SD RRDataset MM-FakeBench

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