mlsanityData to 14 Oct 2026

DF-Net: The Digital Forensics Network for Image Forgery Detection

arXiv 2503.22398 ↗First posted 28 Mar 2025cs.CVcited by 2

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Abstract (arXiv)

The orchestrated manipulation of public opinion, particularly through manipulated images, often spread via online social networks (OSN), has become a serious threat to society. In this paper we introduce the Digital Forensics Net (DF-Net), a deep neural network for pixel-wise image forgery detection. The released model outperforms several state-of-the-art methods on four established benchmark datasets. Most notably, DF-Net's detection is robust against lossy image operations (e.g resizing, compression) as they are automatically performed by social networks.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 21 references that are in the map. First posted on arXiv 28 Mar 2025.

Builds on

5 of 21 references.

References · 5

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2020Media Forensics and DeepFakes: an overviewcited by 209
  4. 2018Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blockscited by 76
  5. 2019Forensic Similarity for Digital Imagescited by 27

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.