mlsanityData to 7 Oct 2026

TALL: Thumbnail Layout for Deepfake Video Detection

arXiv 2307.07494 ↗First posted 14 Jul 2023cs.CVcited by 100

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Abstract (arXiv)

The growing threats of deepfakes to society and cybersecurity have raised enormous public concerns, and increasing efforts have been devoted to this critical topic of deepfake video detection. Existing video methods achieve good performance but are computationally intensive. This paper introduces a simple yet effective strategy named Thumbnail Layout (TALL), which transforms a video clip into a pre-defined layout to realize the preservation of spatial and temporal dependencies. Specifically, consecutive frames are masked in a fixed position in each frame to improve generalization, then resized to sub-images and rearranged into a pre-defined layout as the thumbnail. TALL is model-agnostic and extremely simple by only modifying a few lines of code. Inspired by the success of vision transformers, we incorporate TALL into Swin Transformer, forming an efficient and effective method TALL-Swin. Extensive experiments on intra-dataset and cross-dataset validate the validity and superiority of TALL and SOTA TALL-Swin. TALL-Swin achieves 90.79% AUC on the challenging cross-dataset task, FaceForensics++ → Celeb-DF. The code is available at https://github.com/rainy-xu/TALL4Deepfake.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). Builds on 82 of its 109 references that are in the map. First posted on arXiv 14 Jul 2023.

Builds on

82 of 109 references.

References · 82

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38 more
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  20. 2018Exposing Deep Fakes Using Inconsistent Head Posescited by 294
  21. 2020Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detectioncited by 286
  22. 2020What makes fake images detectable? Understanding properties that generalizecited by 272
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  24. 2020DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectioncited by 251
  25. 2020The Creation and Detection of Deepfakes: A Surveycited by 246
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Citing papers per year: 2023: 5; 2024: 29; 2025: 36; 2026: 30.

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  1. 2024Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detectioncited by 102
  2. 2024DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmarkcited by 85
  3. 2024Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuningcited by 57
  4. 2024FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledgecited by 48
  5. 2023Towards General Visual-Linguistic Face Forgery Detectioncited by 45
  6. 2024On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detectioncited by 40
  7. 2025Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detectorcited by 38
  8. 2024Towards More General Video-based Deepfake Detection through Facial Component Guided Adaptation for Foundation Modelcited by 37
  9. 2024X2-DFD: A framework for eXplainable and eXtendable Deepfake Detectioncited by 35
  10. 2025AI-Generated Video Detection via Perceptual Straighteningcited by 34
  11. 2025D3: Training-Free AI-Generated Video Detection Using Second-Order Featurescited by 32
  12. 2024Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detectioncited by 30
38 more
  1. 2024Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detectioncited by 30
  2. 2024DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusioncited by 29
  3. 2025GenVidBench: A 6-Million Benchmark for AI-Generated Video Detectioncited by 23
  4. 2024Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Contentcited by 22
  5. 2024Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detectioncited by 21
  6. 2024FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learningcited by 21
  7. 2025Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detectioncited by 20
  8. 2024Generative Unlearning for Any Identitycited by 19
  9. 2025Learning Human-Perceived Fakeness in AI-Generated Videos via Multimodal LLMscited by 16
  10. 2025From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakescited by 14
  11. 2026Your One-Stop Solution for AI-Generated Video Detectioncited by 13
  12. 2026VideoVeritas: AI-Generated Video Detection via Perception Pretext Reinforcement Learningcited by 11
  13. 2024Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlookcited by 10
  14. 2025TalkingHeadBench: A Multi-Modal Benchmark & Analysis of Talking-Head DeepFake Detectioncited by 10
  15. 2025MAVOS-DD: Multilingual Audio-Video Open-Set Deepfake Detection Benchmarkcited by 9
  16. 2023DomainForensics: Exposing Face Forgery across Domains via Bi-directional Adaptationcited by 8
  17. 2024Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Methodcited by 8
  18. 2024ED4: Explicit Data-level Debiasing for Deepfake Detectioncited by 8
  19. 2025Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detectioncited by 8
  20. 2026Preserving Forgery Artifacts: AI-Generated Video Detection at Native Scalecited by 8
  21. 2023An adversarial attack approach for eXplainable AI evaluation on deepfake detection modelscited by 7
  22. 2025GenWorld: Towards Detecting AI-generated Real-world Simulation Videoscited by 7
  23. 2025DeepShield: Fortifying Deepfake Video Detection with Local and Global Forgery Analysiscited by 7
  24. 2024Evolving from Single-modal to Multi-modal Facial Deepfake Detection: Progress and Challengescited by 6
  25. 2024FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detectioncited by 6
  26. 2025CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillationcited by 6
  27. 2023Vision-Language Models Learn Super Images for Efficient Partially Relevant Video Retrievalcited by 5
  28. 2026On the Holistic Approach for Detecting Human Image Forgerycited by 5
  29. 2024Compressed Deepfake Video Detection Based on 3D Spatiotemporal Trajectoriescited by 4
  30. 2024Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approachcited by 4
  31. 2024A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoningcited by 4
  32. 2024A Quality-Centric Framework for Generic Deepfake Detectioncited by 4
  33. 2024Passive Deepfake Detection Across Multi-modalities: A Comprehensive Surveycited by 4
  34. 2024UniForensics: Face Forgery Detection via General Facial Representationcited by 3
  35. 2025FakeParts: a New Family of AI-Generated DeepFakescited by 3
  36. 2025AuViRe: Audio-visual Speech Representation Reconstruction for Deepfake Temporal Localizationcited by 3
  37. 2024Tex-ViT: A Generalizable, Robust, Texture-based dual-branch cross-attention deepfake detectorcited by 2
  38. 2024FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Preventioncited by 2

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