journal article·2025Open access

Deepfake Detection Method Based on Spatio-Temporal Information Fusion

Xinyi Wang, Wanru Song, Chuanyan Hao, Feng Liu

Computers, Materials & Continua· Volume 83· Issue 2

Abstract

As Deepfake technology continues to evolve, the distinction between real and fake content becomes increasingly blurred. Most existing Deepfake video detection methods rely on single-frame facial image features, which limits t... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Anomaly Detection Techniques and Applications · Digital Media Forensic Detection

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (37)

Show source-provided references
1. Deepfake. [cited 2019 Oct 29]. Available from: http://github.com/deepfakes/faceswap.
2. Generative adversarial networks: an overview10.1109/MSP.2017.2765202 ↗
3. Kingma DP, Welling M. Auto-encoding variational Bayes. arXiv:1312.6114. 2013.
4. SemanticStyleGAN: learning compositional generative priors for controllable image synthesis and editing
5. Wang Y, Chen X, Zhu J, Chu W, Tai Y, Wang C, et al. HifiFace: 3D shape and semantic prior guided high fidelity face swapping. arXiv:2106.09965. 2021.10.24963/ijcai.2021/157 ↗
6. Review of deep network generative fake face detection methods
7. Exposing digital forgeries by detecting traces of resampling10.1109/TSP.2004.839932 ↗
8. Exploiting visual artifacts to expose deepfakes and face manipulations
9. Pishori A, Rollins B, van Houten N, Chatwani N, Uraimov O. Detecting Deepfake videos: an analysis of three techniques. arXiv:2007.08517. 2020.
10. Deepfake detection by analyzing convolutional traces
11. FakeCatcher: detection of synthetic portrait videos using biological signals
12. In ictu oculi: exposing AI-created fake videos by detecting eye blinking
13. Face X-ray for more general face forgery detection
14. A study on face anti-spoofing based on semi-supervised learning
15. Face forgery detection by 3D decomposition
16. Mesonet: a compact facial video forgery detection network
17. Chugh K, Gupta P, Dhall A, Subramanian R. Not made for each other Audio-visual dissonance-based deepfake detection and localization. arXiv:2007.08517. 2020.10.1145/3394171.3413700 ↗
18. Multi-branch deepfake detection algorithm based on fine-grained features
19. Capsule-forensics: using capsule networks to detect forged images and videos
20. Multi-task learning for detecting and segmenting manipulated facial images and videos
21. Deepfake detection based on discrepancies between faces and their context10.1109/TPAMI.2021.3093446 ↗
22. Multi-attentional deepfake detection
23. M2tr: multi-modal multi-scale transformers for deepfake detection
24. Keresh A, Shamoi P. Liveness detection in computer vision: transformer-based self-supervised learning for face anti-spoofing. arXiv:2406.138602024. 2024.10.1109/ACCESS.2024.3513795 ↗
25. Exposing deepfake videos by detecting face warping artifacts
26. Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, et al. An image is worth 16 × 16 words: transformers for image recognition at scale. arXiv:2010.11929. 2020.
27. FakeApp. [cited 2025 Jan 1]. Available from: https://www.fakeapp.org/download.
28. SegNet: a deep convolutional encoder-decoder architecture for image segmentation10.1109/TPAMI.2016.2644615 ↗
29. DeepFaceLab. [cited 2023 Oct 3]. Available from: http://github.com/iperov/DeepFaceLab.
30. DFaker. [cited 2022 May 1]. Available from: http://github.com/dfaker/df.
31. A robust approach to multimodal deepfake detection10.3390/jimaging9060122 ↗
32. Detecting deepfakes: using CNN to identify manipulated visual media
33. Attention is all you need
34. Quo Vadis, action recognition? A new model and the kinetics dataset
35. FaceForensics++: learning to detect manipulated facial images
36. Celeb-DF: a large-scale challenging dataset for deepfake forensics
37. Motion magnified 3-D residual-in-dense network for deepfake detection10.1109/TBIOM.2022.3201887 ↗