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Enhancing Multimodal Deepfake Detection With Local-Global Feature Integration and Diffusion Models by adhokshjavali11 is a document available to read on EtoBox.

This paper presents an advanced multimodal framework for deepfake detection that integrates local and global feature extraction using Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), respectively. The approach enhances detection accuracy by incorporating additional visual features such as eye movements and facial regions, alongside audio features, while utilizing diffusion models to refine input data quality. The proposed method achieves state-of-the-art performance on multiple datasets,

Author

adhokshjavali11

Language

EN