BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection
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Abstract (arXiv)
The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of those images. Thus, it is important to develop a generalized detector for synthesized images of any GAN model or object category, including those unseen during the training phase. However, the conventional methods heavily depend on the training settings, which cause a dramatic decline in performance when tested with unknown domains. To resolve the issue and obtain a generalized detection ability, we propose Bilateral High-Pass Filters (BiHPF), which amplify the effect of the frequency-level artifacts that are known to be found in the synthesized images of generative models. Numerous experimental results validate that our method outperforms other state-of-the-art methods, even when tested with unseen domains.
Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). Builds on 27 of its 46 references that are in the map. First posted on arXiv 16 Aug 2021.
Builds on
27 of 46 references.
References · 27
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15 more
- 2019Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensicscited by 573
- 2020Leveraging Frequency Analysis for Deep Fake Image Recognitioncited by 501
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- 2020Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributionscited by 278
- 2019On the Detection of Digital Face Manipulationcited by 259
- 2019The Deepfake Detection Challenge (DFDC) Preview Datasetcited by 208
- 2018Do GANs leave artificial fingerprints?cited by 188
- 2018Fighting Fake News: Image Splice Detection via Learned Self-Consistencycited by 136
- 2018ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detectioncited by 104
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- 2020Deepfakes Detection with Automatic Face Weightingcited by 35
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Citing papers per year: 2022: 4; 2023: 6; 2024: 15; 2025: 21; 2026: 14.
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- 2026DRIFT: From Robustness Gaps to Invariance Manifolds for AI-Generated Image Detection5 Jun 2026
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- 2026SpecSem-Net: Integrating Spectral and Semantic Features for Robust AI-generated Video Detection17 May 2026
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- 2026Detecting AI-Generated Images via Distributional Deviations from Real Images7 Jan 2026
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