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Multi-Scale Wavelet Transformer for Face Forgery Detection. (arXiv:2210.03899v1 [cs.CV])
Oct. 11, 2022, 1:17 a.m. | Jie Liu, Jingjing Wang, Peng Zhang, Chunmao Wang, Di Xie, Shiliang Pu
cs.CV updates on arXiv.org arxiv.org
Currently, many face forgery detection methods aggregate spatial and
frequency features to enhance the generalization ability and gain promising
performance under the cross-dataset scenario. However, these methods only
leverage one level frequency information which limits their expressive ability.
To overcome these limitations, we propose a multi-scale wavelet transformer
framework for face forgery detection. Specifically, to take full advantage of
the multi-scale and multi-frequency wavelet representation, we gradually
aggregate the multi-scale wavelet representation at different stages of the
backbone network. To …
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