When deepfakes are widespread on chatting platforms, they are expected to be subject to heavy resizing and compressing steps. In this paper, we present a tensor-based representation of compressed and resized images. Tensor embeds DCT features computed on multi-scaled and multi-compressed versions of the input facial image. Moreover, a custom deep-architecture is designed and trained on the proposed representation. Experimental results show its pros and cons with respect to state-of-the-art methods.

Tensor-Based Deepfake Detection in Scaled and Compressed Images

Sara Concas;Gianpaolo Perelli;Gian Luca Marcialis;Giovanni Puglisi
2022-01-01

Abstract

When deepfakes are widespread on chatting platforms, they are expected to be subject to heavy resizing and compressing steps. In this paper, we present a tensor-based representation of compressed and resized images. Tensor embeds DCT features computed on multi-scaled and multi-compressed versions of the input facial image. Moreover, a custom deep-architecture is designed and trained on the proposed representation. Experimental results show its pros and cons with respect to state-of-the-art methods.
2022
Deepfake
face
biometric
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/404704
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