mlsanityData to 7 Oct 2026

Fake Generated Painting Detection via Frequency Analysis

arXiv 2003.02467 ↗First posted 5 Mar 2020cs.CVcited by 6

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Abstract (arXiv)

With the development of deep neural networks, digital fake paintings can be generated by various style transfer algorithms.To detect the fake generated paintings, we analyze the fake generated and real paintings in Fourier frequency domain and observe statistical differences and artifacts. Based on our observations, we propose Fake Generated Painting Detection via Frequency Analysis (FGPD-FA) by extracting three types of features in frequency domain. Besides, we also propose a digital fake painting detection database for assessing the proposed method. Experimental results demonstrate the excellence of the proposed method in different testing conditions.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Mar 2020.

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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1; 2025: 1.

6 papers.