mlsanityData to 7 Oct 2026

MikuDance: Animating Character Art with Mixed Motion Dynamics

arXiv 2411.08656 ↗First posted 13 Nov 2024cs.CVcited by 7

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Abstract (arXiv)

We propose MikuDance, a diffusion-based pipeline incorporating mixed motion dynamics to animate stylized character art. MikuDance consists of two key techniques: Mixed Motion Modeling and Mixed-Control Diffusion, to address the challenges of high-dynamic motion and reference-guidance misalignment in character art animation. Specifically, a Scene Motion Tracking strategy is presented to explicitly model the dynamic camera in pixel-wise space, enabling unified character-scene motion modeling. Building on this, the Mixed-Control Diffusion implicitly aligns the scale and body shape of diverse characters with motion guidance, allowing flexible control of local character motion. Subsequently, a Motion-Adaptive Normalization module is incorporated to effectively inject global scene motion, paving the way for comprehensive character art animation. Through extensive experiments, we demonstrate the effectiveness and generalizability of MikuDance across various character art and motion guidance, consistently producing high-quality animations with remarkable motion dynamics.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 40 of its 51 references that are in the map. First posted on arXiv 13 Nov 2024.

Builds on

40 of 51 references.

References · 40

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  5. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  7. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  8. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  9. 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,418
  10. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,295
  11. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
  12. 2022Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generationcited by 958
28 more
  1. 2020First Order Motion Model for Image Animationcited by 698
  2. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 683
  3. 2021DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Camerascited by 673
  4. 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generationcited by 530
  5. 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 463
  6. 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 448
  7. 2023MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Modelcited by 330
  8. 2023Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videoscited by 312
  9. 2022EDGE: Editable Dance Generation From Musiccited by 284
  10. 2024Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidancecited by 271
  11. 2023DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectorycited by 260
  12. 2024LivePortrait: Efficient Portrait Animation with Stitching and Retargeting Controlcited by 202
  13. 2023DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusioncited by 167
  14. 2024Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motioncited by 167
  15. 2024CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generationcited by 163
  16. 2019Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesiscited by 161
  17. 2023DisCo: Disentangled Control for Realistic Human Dance Generationcited by 141
  18. 2023MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusioncited by 115
  19. 2022Person Image Synthesis via Denoising Diffusion Modelcited by 104
  20. 2024UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animationcited by 101
  21. 2023Generative Image Dynamicscited by 93
  22. 2024MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Modelcited by 87
  23. 2024Animate-X: Universal Character Image Animation with Enhanced Motion Representationcited by 86
  24. 2023AnimateAnything: Fine-Grained Open Domain Image Animation with Motion Guidancecited by 66
  25. 2024HumanVid: Demystifying Training Data for Camera-controllable Human Image Animationcited by 63
  26. 2024Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimatorscited by 39
  27. 2024RealisDance: Equip controllable character animation with realistic handscited by 37
  28. 2023X-Pose: Detecting Any Keypointscited by 21

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.