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In this paper, we propose a novel video transformer with incremental learning for detecting deepfake videos The convolutional vision transformer has two components:. To better align the input face images, we use a 3d face.

A method, apparatus, and system for detecting deepfake videos, includes an input device for inputting a potential deepfake video, the input device inputs a sequence of video frames of. In this work, we propose a convolutional vision transformer for the detection of deepfakes This paper proposes a video transformer model with incremental learning for deepfake detection

It uses 3d face reconstruction to generate uv texture maps, incorporating both face images.

In this work, we propose a generative convolutional vision transformer (genconvit) for deepfake video detection Our model combines convnext and swin. Computer vision and pattern recognition

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