Detection of Digital Facial Retouching utilizing Face Beauty Information
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Abstract (arXiv)
Facial retouching to beautify images is widely spread in social media, advertisements, and it is even applied in professional photo studios to let individuals appear younger, remove wrinkles and skin impurities. Generally speaking, this is done to enhance beauty. This is not a problem itself, but when retouched images are used as biometric samples and enrolled in a biometric system, it is one. Since previous work has proven facial retouching to be a challenge for face recognition systems,the detection of facial retouching becomes increasingly necessary. This work proposes to study and analyze changes in beauty assessment algorithms of retouched images, assesses different feature extraction methods based on artificial intelligence in order to improve retouching detection, and evaluates whether face beauty can be exploited to enhance the detection rate. In a scenario where the attacking retouching algorithm is unknown, this work achieved 1.1% D-EER on single image detection.
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References · 12
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- 2019GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detectioncited by 42
- 2018SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Predictioncited by 33
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- 2023Face Feature Visualisation of Single Morphing Attack Detectioncited by 8
- 2019Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Levelcited by 6
- 2018Transferring Rich Deep Features for Facial Beauty Predictioncited by 5
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