Super-resolution Reconstruction Detection Method for DeepFake Hard Compressed Videos

Lei SUN; Hongmeng ZHANG; Xiuqing MAO; Song GUO; Yongjin HU

doi:10.11999/JEIT200531

Volume 43 Issue 10

Oct. 2021

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Lei SUN, Hongmeng ZHANG, Xiuqing MAO, Song GUO, Yongjin HU. Super-resolution Reconstruction Detection Method for DeepFake Hard Compressed Videos[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2967-2975. doi: 10.11999/JEIT200531

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Lei SUN, Hongmeng ZHANG, Xiuqing MAO, Song GUO, Yongjin HU. Super-resolution Reconstruction Detection Method for DeepFake Hard Compressed Videos[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2967-2975. doi: 10.11999/JEIT200531

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Super-resolution Reconstruction Detection Method for DeepFake Hard Compressed Videos

doi: 10.11999/JEIT200531

PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China

Funds: The National Key R&D Program of China (2017YFB0801900)

Received Date: 2020-06-30
Rev Recd Date: 2020-12-31

Available Online: 2021-02-02

Publish Date: 2021-10-18

Abstract

Abstract

The forensics methods of DeepFake video generally use convolution neural networks. However, these methods perform poorly on hard compressed DeepFake datasets and make a large number of false detections on real data. To solve the problem above, a method of hard compressed DeepFake video detection based on deep neural network model is proposed, which improves the detection accuracy of hard compressed video by incorporating super-resolution reconstruction technology and recovering the loss of the spatial and temporal information during hard compression. Experiments are performed with the FaceForensics++ Datasets and DFDC (the DeepFake Detection Challenge) Datasets for hard compressed DeepFake video, which improve the test accuracy of single frame and video compared to ResNet50, and effectively alleviate the problem of false detection of real video with hard compression.
- DeepFake detection,
- Super resolution reconstruction,
- Video hard compression,
- Deep learning

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References(21)

References

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