DEEPFAKE DETECTION VIA SEPARABLE SELF-CONSISTENCY LEARNING SUPPLEMENTARY MATERIAL

DOI:: 10.60864/9k1a-dd61
Citation Author(s):: Lin Lu

Lin Lu, Yunhong Wang, Wenqi Zhuo, Liang Zhang, Guangshuai Gao, Yuanfang Guo
Submitted by:: Lin Lu
Last updated:: 8 February 2024 - 4:56am
Document Type:: Supplementary material

Categories:: Multimedia Forensics

This document provides a supplementary material called "Deepfake Detection via Separable Self-Consistency Learning" submitted to the regular track of the ICIP 2024. The document contains the video-Level comprehensive results, frame-level results.

DEEPFAKE DETECTION VIA SEPARABLE SELF-CONSISTENCY LEARNING SUPPLEMENTARY MATERIAL.pdf

DEEPFAKE DETECTION VIA SEPARABLE SELF-CONSISTENCY LEARNING SUPPLEMENTARY MATERIAL.pdf (78)

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Supplementary material

DEEPFAKE DETECTION VIA SEPARABLE SELF-CONSISTENCY LEARNING SUPPLEMENTARY MATERIAL

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