mlsanityData to 7 Oct 2026

Deepfake Detection using Spatiotemporal Convolutional Networks

arXiv 2006.14749 ↗First posted 26 Jun 2020cs.CV cs.LG eess.IVcited by 32

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Abstract (arXiv)

Better generative models and larger datasets have led to more realistic fake videos that can fool the human eye but produce temporal and spatial artifacts that deep learning approaches can detect. Most current Deepfake detection methods only use individual video frames and therefore fail to learn from temporal information. We created a benchmark of the performance of spatiotemporal convolutional methods using the Celeb-DF dataset. Our methods outperformed state-of-the-art frame-based detection methods. Code for our paper is publicly available at https://github.com/oidelima/Deepfake-Detection.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jun 2020.

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Citing papers per year: 2021: 8; 2022: 9; 2023: 7; 2024: 2; 2025: 4; 2026: 2.

32 papers.

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  1. 2021Exploring Temporal Coherence for More General Video Face Forgery Detectioncited by 158
  2. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
  3. 2021Combining EfficientNet and Vision Transformers for Video Deepfake Detectioncited by 81
  4. 2023AltFreezing for More General Video Face Forgery Detectioncited by 78
  5. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  6. 2023Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localizationcited by 42
  7. 2021Video Transformer for Deepfake Detection with Incremental Learningcited by 33
  8. 2023Quality-Agnostic Deepfake Detection with Intra-model Collaborative Learningcited by 32
  9. 2021Deepfake Detection Scheme Based on Vision Transformer and Distillationcited by 22
  10. 2022Model Attribution of Face-swap Deepfake Videoscited by 17
  11. 20223D-Aware Video Generationcited by 17
  12. 2022FedForgery: Generalized Face Forgery Detection with Residual Federated Learningcited by 12
20 more
  1. 2022A Hybrid CNN-LSTM model for Video Deepfake Detection by Leveraging Optical Flow Featurescited by 7
  2. 2021Deep Semantic Manipulation of Facial Videoscited by 6
  3. 2022Using Deep Learning to Detecting Deepfakescited by 6
  4. 2025SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detectioncited by 6
  5. 2022Cross-Domain Local Characteristic Enhanced Deepfake Video Detectioncited by 4
  6. 2023CapST: Leveraging Capsule Networks and Temporal Attention for Accurate Model Attribution in Deep-fake Videoscited by 3
  7. 2024A Multimodal Framework for Deepfake Detectioncited by 3
  8. 2023Leveraging Deep Learning Approaches for Deepfake Detection: A Reviewcited by 2
  9. 2025Reduced Spatial Dependency for More General Video-level Deepfake Detectioncited by 2
  10. 2025Detecting Localized Deepfake Manipulations Using Action Unit-Guided Video Representationscited by 2
  11. 2025FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakescited by 2
  12. 2023Facial Forgery-based Deepfake Detection using Fine-Grained Featurescited by 1
  13. 2023Unearthing Common Inconsistency for Generalisable Deepfake Detectioncited by 1
  14. 2021Challenges and Solutions in DeepFakescited by 0
  15. 2022Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localizationcited by 0
  16. 2022DF-Captcha: A Deepfake Captcha for Preventing Fake Callscited by 0
  17. 2022A Machine Learning Approach for DeepFake Detectioncited by 0
  18. 2024Learning Expressive And Generalizable Motion Features For Face Forgery Detectioncited by 0
  19. 2026Deepfake Forensics Adapter: A Dual-Stream Network for Generalizable Deepfake Detectioncited by 0
  20. 2026Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attackscited by 0