920 research outputs found
Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection
Local descriptors based on the image noise residual have proven extremely
effective for a number of forensic applications, like forgery detection and
localization. Nonetheless, motivated by promising results in computer vision,
the focus of the research community is now shifting on deep learning. In this
paper we show that a class of residual-based descriptors can be actually
regarded as a simple constrained convolutional neural network (CNN). Then, by
relaxing the constraints, and fine-tuning the net on a relatively small
training set, we obtain a significant performance improvement with respect to
the conventional detector
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