mlsanityData to 14 Oct 2026

FairyGen: Storied Cartoon Video from a Single Child-Drawn Character

arXiv 2506.21272 ↗First posted 26 Jun 2025cs.GR cs.CV cs.MMcited by 4

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Abstract (arXiv)

We propose FairyGen, an automatic system for generating story-driven cartoon videos from a single child's drawing, while faithfully preserving its unique artistic style. Unlike previous storytelling methods that primarily focus on character consistency and basic motion, FairyGen explicitly disentangles character modeling from stylized background generation and incorporates cinematic shot design to support expressive and coherent storytelling. Given a single character sketch, we first employ an MLLM to generate a structured storyboard with shot-level descriptions that specify environment settings, character actions, and camera perspectives. To ensure visual consistency, we introduce a style propagation adapter that captures the character's visual style and applies it to the background, faithfully retaining the character's full visual identity while synthesizing style-consistent scenes. A shot design module further enhances visual diversity and cinematic quality through frame cropping and multi-view synthesis based on the storyboard. To animate the story, we reconstruct a 3D proxy of the character to derive physically plausible motion sequences, which are then used to fine-tune an MMDiT-based image-to-video diffusion model. We further propose a two-stage motion customization adapter: the first stage learns appearance features from temporally unordered frames, disentangling identity from motion; the second stage models temporal dynamics using a timestep-shift strategy with frozen identity weights. Once trained, FairyGen directly renders diverse and coherent video scenes aligned with the storyboard. Extensive experiments demonstrate that our system produces animations that are stylistically faithful, narratively structured natural motion, highlighting its potential for personalized and engaging story animation. The code will be available at https://github.com/GVCLab/FairyGen

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 43 of its 60 references that are in the map. First posted on arXiv 26 Jun 2025.

Builds on

43 of 60 references.

References · 43

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
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  6. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
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  8. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
  9. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
  10. 2023VBench: Comprehensive Benchmark Suite for Video Generative Modelscited by 1,822
  11. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,660
  12. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,106
31 more
  1. 2024VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Modelscited by 579
  2. 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generationcited by 535
  3. 2023EvalCrafter: Benchmarking and Evaluating Large Video Generation Modelscited by 340
  4. 2025ReCamMaster: Camera-Controlled Generative Rendering from A Single Videocited by 287
  5. 2024StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generationcited by 247
  6. 2024BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusioncited by 202
  7. 2023StyleDrop: Text-to-Image Generation in Any Stylecited by 199
  8. 2023DreamVideo: Composing Your Dream Videos with Customized Subject and Motioncited by 188
  9. 2018StoryGAN: A Sequential Conditional GAN for Story Visualizationcited by 138
  10. 2023VideoBooth: Diffusion-based Video Generation with Image Promptscited by 126
  11. 2024MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequencecited by 89
  12. 2024Animate-X: Universal Character Image Animation with Enhanced Motion Representationcited by 88
  13. 2022Make-A-Story: Visual Memory Conditioned Consistent Story Generationcited by 76
  14. 2023TaleCrafter: Interactive Story Visualization with Multiple Characterscited by 73
  15. 2024Vlogger: Make Your Dream A Vlogcited by 70
  16. 2023Inserting Anybody in Diffusion Models via Celeb Basiscited by 63
  17. 2023Putting People in Their Place: Affordance-Aware Human Insertion into Scenescited by 53
  18. 2024DreamStory: Open-Domain Story Visualization by LLM-Guided Multi-Subject Consistent Diffusioncited by 47
  19. 2025One Model to Rig Them All: Diverse Skeleton Rigging with UniRigcited by 45
  20. 2023MEVG: Multi-event Video Generation with Text-to-Video Modelscited by 40
  21. 2023AutoStory: Generating Diverse Storytelling Images with Minimal Human Effortcited by 38
  22. 2022Character-Centric Story Visualization via Visual Planning and Token Alignmentcited by 33
  23. 2022Word-Level Fine-Grained Story Visualizationcited by 23
  24. 2023A Method for Animating Children's Drawings of the Human Figurecited by 20
  25. 2024StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completioncited by 20
  26. 2025Dynamic Concepts Personalization from Single Videoscited by 20
  27. 2024StoryWeaver: A Unified World Model for Knowledge-Enhanced Story Character Customizationcited by 10
  28. 2024DrawingSpinUp: 3D Animation from Single Character Drawingscited by 9
  29. 2023CogCartoon: Towards Practical Story Visualizationcited by 8
  30. 2024ActAnywhere: Subject-Aware Video Background Generationcited by 8
  31. 2023Make-A-Storyboard: A General Framework for Storyboard with Disentangled and Merged Controlcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026DreamShot: Personalized Storyboard Synthesis with Video Diffusion Prior
  2. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation
  3. 2023Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion Models
  4. 2026AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist?
  5. 2024CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization
  6. 2025Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions
  7. 2025AnimeShooter: A Multi-Shot Animation Dataset for Reference-Guided Video Generation
  8. 2024DreamRunner: Fine-Grained Compositional Story-to-Video Generation with Retrieval-Augmented Motion Adaptation