mlsanityData to 7 Oct 2026

Everybody Dance Now

arXiv 1808.07371 ↗First posted 22 Aug 2018cs.GR cs.CVcited by 313

Not on the map. Why?

Cited by 39 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing, we can transfer that performance to a novel (amateur) target after only a few minutes of the target subject performing standard moves. We approach this problem as video-to-video translation using pose as an intermediate representation. To transfer the motion, we extract poses from the source subject and apply the learned pose-to-appearance mapping to generate the target subject. We predict two consecutive frames for temporally coherent video results and introduce a separate pipeline for realistic face synthesis. Although our method is quite simple, it produces surprisingly compelling results (see video). This motivates us to also provide a forensics tool for reliable synthetic content detection, which is able to distinguish videos synthesized by our system from real data. In addition, we release a first-of-its-kind open-source dataset of videos that can be legally used for training and motion transfer.

Key facts. Cited by 313 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Aug 2018.

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Citing papers per year: 2021: 104; 2022: 66; 2023: 43; 2024: 44; 2025: 38; 2026: 18.

313 papers.

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  1. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 683
  2. 2022HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Videocited by 483
  3. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  4. 2023MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Modelcited by 330
  5. 2023Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videoscited by 312
  6. 2024Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidancecited by 271
  7. 2023DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectorycited by 260
  8. 2023GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussianscited by 256
  9. 2021Motion Representations for Articulated Animationcited by 253
  10. 2024Sapiens: Foundation for Human Vision Modelscited by 229
  11. 2022Thin-Plate Spline Motion Model for Image Animationcited by 209
  12. 2021Neural Articulated Radiance Fieldcited by 196
38 more
  1. 2024MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidancecited by 196
  2. 2023Conditional Image-to-Video Generation with Latent Flow Diffusion Modelscited by 180
  3. 2022Latent Image Animator: Learning to Animate Images via Latent Space Navigationcited by 172
  4. 2021A Good Image Generator Is What You Need for High-Resolution Video Synthesiscited by 162
  5. 2021Editable Free-viewpoint Video Using a Layered Neural Representationcited by 148
  6. 2022StyleGAN-Human: A Data-Centric Odyssey of Human Generationcited by 143
  7. 2023DisCo: Disentangled Control for Realistic Human Dance Generationcited by 141
  8. 2021Taming Visually Guided Sound Generationcited by 136
  9. 2021Real-time Deep Dynamic Characterscited by 133
  10. 2023Space-Time Diffusion Features for Zero-Shot Text-Driven Motion Transfercited by 124
  11. 2023MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusioncited by 115
  12. 2021A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representationcited by 113
  13. 2023Affordance Diffusion: Synthesizing Hand-Object Interactionscited by 110
  14. 2021Animatable Neural Radiance Fields from Monocular RGB Videoscited by 109
  15. 2021Neural Actor: Neural Free-view Synthesis of Human Actors with Pose Controlcited by 106
  16. 2021FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learningcited by 90
  17. 2021Make It Move: Controllable Image-to-Video Generation with Text Descriptionscited by 88
  18. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
  19. 2021Driving-Signal Aware Full-Body Avatarscited by 81
  20. 2021GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Drivingcited by 75
  21. 2021DG-Font: Deformable Generative Networks for Unsupervised Font Generationcited by 70
  22. 2021CCVS: Context-aware Controllable Video Synthesiscited by 68
  23. 2023Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenescited by 68
  24. 2021Modeling Clothing as a Separate Layer for an Animatable Human Avatarcited by 66
  25. 2022Synthetic Data -- what, why and how?cited by 66
  26. 2022Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representationscited by 65
  27. 2021Playable Video Generationcited by 63
  28. 2024HumanVid: Demystifying Training Data for Camera-controllable Human Image Animationcited by 63
  29. 2021Disentangled Cycle Consistency for Highly-realistic Virtual Try-Oncited by 62
  30. 2022Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Productioncited by 61
  31. 2025Animate Anyone 2: High-Fidelity Character Image Animation with Environment Affordancecited by 60
  32. 2021Neural Re-Rendering of Humans from a Single Imagecited by 59
  33. 2021Speech Drives Templates: Co-Speech Gesture Synthesis with Learned Templatescited by 57
  34. 2022Look Outside the Room: Synthesizing A Consistent Long-Term 3D Scene Video from A Single Imagecited by 55
  35. 2022Audio-Driven Co-Speech Gesture Video Generationcited by 54
  36. 2023Learning Locally Editable Virtual Humanscited by 54
  37. 2021Style and Pose Control for Image Synthesis of Humans from a Single Monocular Viewcited by 53
  38. 2023Text2Performer: Text-Driven Human Video Generationcited by 53

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