# Digital Media Forensic Detection

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/digital-media-forensic-detection/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the detection and identification of digital image forgeries, including techniques such as copy-move forgery detection, sensor pattern noise analysis, JPEG compression history estimation, camera model identification, splicing detection, and tampering localization. The papers also explore the application of deep learning methods for image forensics and the detection of inconsistencies in image manipulation. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12357 |
| Works | 91 |

## Topic papers all

Showing 15 of 91.

- [MesoNet: a Compact Facial Video Forgery Detection Network](https://scholariq.org/papers/mesonet-a-compact-facial-video-forgery-detection-network/)
- [Capsule-forensics: Using Capsule Networks to Detect Forged Images and Videos](https://scholariq.org/papers/capsule-forensics-using-capsule-networks-to-detect-forged-images-and-videos/)
- [Face Recognition in Poor-Quality Video: Evidence From Security Surveillance](https://scholariq.org/papers/face-recognition-in-poor-quality-video-evidence-from-security-surveillance/)
- [Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos](https://scholariq.org/papers/multi-task-learning-for-detecting-and-segmenting-manipulated-facial-images-and/)
- [Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward](https://scholariq.org/papers/deepfakes-generation-and-detection-state-of-the-art-open-challenges/)
- [Deep learning for deepfakes creation and detection: A survey](https://scholariq.org/papers/deep-learning-for-deepfakes-creation-and-detection-a-survey/)
- [Distinguishing computer graphics from natural images using convolution neural networks](https://scholariq.org/papers/distinguishing-computer-graphics-from-natural-images-using-convolution-neural/)
- [Digital Signal Modulation Classification With Data Augmentation Using Generative Adversarial Nets in Cognitive Radio Networks](https://scholariq.org/papers/digital-signal-modulation-classification-with-data-augmentation-using-generative/)
- [Digital image steganography: A literature survey](https://scholariq.org/papers/digital-image-steganography-a-literature-survey/)
- [Recent Advances of Generative Adversarial Networks in Computer Vision](https://scholariq.org/papers/recent-advances-of-generative-adversarial-networks-in-computer-vision/)
- [Secure and Robust Digital Image Watermarking Using Coefficient Differencing and Chaotic Encryption](https://scholariq.org/papers/secure-and-robust-digital-image-watermarking-using-coefficient-differencing-and/)
- [An Optimized Image Watermarking Method Based on HD and SVD in DWT Domain](https://scholariq.org/papers/an-optimized-image-watermarking-method-based-on-hd-and-svd-in-dwt-domain/)
- [Detecting Recompression of JPEG Images via Periodicity Analysis of Compression Artifacts for Tampering Detection](https://scholariq.org/papers/detecting-recompression-of-jpeg-images-via-periodicity-analysis-of-compression/)
- [Use of a Capsule Network to Detect Fake Images and Videos](https://scholariq.org/papers/use-of-a-capsule-network-to-detect-fake-images-and-videos/)
- [FusionM4Net: A multi-stage multi-modal learning algorithm for multi-label skin lesion classification](https://scholariq.org/papers/fusionm4net-a-multi-stage-multi-modal-learning-algorithm-for-multi-label-skin/)

## Topic primary papers

Showing 15 of 25.

- [MesoNet: a Compact Facial Video Forgery Detection Network](https://scholariq.org/papers/mesonet-a-compact-facial-video-forgery-detection-network/)
- [Capsule-forensics: Using Capsule Networks to Detect Forged Images and Videos](https://scholariq.org/papers/capsule-forensics-using-capsule-networks-to-detect-forged-images-and-videos/)
- [Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos](https://scholariq.org/papers/multi-task-learning-for-detecting-and-segmenting-manipulated-facial-images-and/)
- [Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward](https://scholariq.org/papers/deepfakes-generation-and-detection-state-of-the-art-open-challenges/)
- [Deep learning for deepfakes creation and detection: A survey](https://scholariq.org/papers/deep-learning-for-deepfakes-creation-and-detection-a-survey/)
- [Distinguishing computer graphics from natural images using convolution neural networks](https://scholariq.org/papers/distinguishing-computer-graphics-from-natural-images-using-convolution-neural/)
- [Detecting Recompression of JPEG Images via Periodicity Analysis of Compression Artifacts for Tampering Detection](https://scholariq.org/papers/detecting-recompression-of-jpeg-images-via-periodicity-analysis-of-compression/)
- [Use of a Capsule Network to Detect Fake Images and Videos](https://scholariq.org/papers/use-of-a-capsule-network-to-detect-fake-images-and-videos/)
- [Face image manipulation detection based on a convolutional neural network](https://scholariq.org/papers/face-image-manipulation-detection-based-on-a-convolutional-neural-network/)
- [Digital multimedia audio forensics: past, present and future](https://scholariq.org/papers/digital-multimedia-audio-forensics-past-present-and-future/)
- [Constructing New Backbone Networks via Space-Frequency Interactive Convolution for Deepfake Detection](https://scholariq.org/papers/constructing-new-backbone-networks-via-space-frequency-interactive-convolution/)
- [Hybrid Image-Retrieval Method for Image-Splicing Validation](https://scholariq.org/papers/hybrid-image-retrieval-method-for-image-splicing-validation/)
- [Digital Face Manipulation Creation and Detection: A Systematic Review](https://scholariq.org/papers/digital-face-manipulation-creation-and-detection-a-systematic-review/)
- [Image Splicing Forgery Detection Using DCT Coefficients with Multi-Scale LBP](https://scholariq.org/papers/image-splicing-forgery-detection-using-dct-coefficients-with-multi-scale-lbp/)
- [A survey of artificial intelligence strategies for automatic detection of sexually explicit videos](https://scholariq.org/papers/a-survey-of-artificial-intelligence-strategies-for-automatic-detection-of/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.