mlsanityData to 14 Oct 2026

Sketch2Anim: Towards Transferring Sketch Storyboards into 3D Animation

arXiv 2504.19189 ↗First posted 27 Apr 2025cs.GR cs.CVcited by 17

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Abstract (arXiv)

Storyboarding is widely used for creating 3D animations. Animators use the 2D sketches in storyboards as references to craft the desired 3D animations through a trial-and-error process. The traditional approach requires exceptional expertise and is both labor-intensive and time-consuming. Consequently, there is a high demand for automated methods that can directly translate 2D storyboard sketches into 3D animations. This task is under-explored to date and inspired by the significant advancements of motion diffusion models, we propose to address it from the perspective of conditional motion synthesis. We thus present Sketch2Anim, composed of two key modules for sketch constraint understanding and motion generation. Specifically, due to the large domain gap between the 2D sketch and 3D motion, instead of directly conditioning on 2D inputs, we design a 3D conditional motion generator that simultaneously leverages 3D keyposes, joint trajectories, and action words, to achieve precise and fine-grained motion control. Then, we invent a neural mapper dedicated to aligning user-provided 2D sketches with their corresponding 3D keyposes and trajectories in a shared embedding space, enabling, for the first time, direct 2D control of motion generation. Our approach successfully transfers storyboards into high-quality 3D motions and inherently supports direct 3D animation editing, thanks to the flexibility of our multi-conditional motion generator. Comprehensive experiments and evaluations, and a user perceptual study demonstrate the effectiveness of our approach.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 41 of its 75 references that are in the map. First posted on arXiv 27 Apr 2025.

Builds on

41 of 75 references.

References · 41

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Implicit Modelscited by 9,781
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  4. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  5. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,351
  6. 2022Human Motion Diffusion Modelcited by 1,080
  7. 2022MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Modelcited by 780
  8. 2023T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representationscited by 588
  9. 2022Executing your Commands via Motion Diffusion in Latent Spacecited by 575
  10. 2023MotionGPT: Human Motion as a Foreign Languagecited by 527
  11. 2022TEMOS: Generating diverse human motions from textual descriptionscited by 492
  12. 2023MoMask: Generative Masked Modeling of 3D Human Motionscited by 400
29 more
  1. 2022TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Textscited by 359
  2. 2023Human Motion Diffusion as a Generative Priorcited by 357
  3. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  4. 2023OmniControl: Control Any Joint at Any Time for Human Motion Generationcited by 238
  5. 2021Robust Motion In-betweeningcited by 229
  6. 2023Guided Motion Diffusion for Controllable Human Motion Synthesiscited by 223
  7. 2023Object Motion Guided Human Motion Synthesiscited by 212
  8. 2023UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wildcited by 200
  9. 2023TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesiscited by 198
  10. 2022MotionBERT: A Unified Perspective on Learning Human Motion Representationscited by 193
  11. 2021Synthesis of Compositional Animations from Textual Descriptionscited by 178
  12. 2024MotionLCM: Real-time Controllable Motion Generation via Latent Consistency Modelcited by 168
  13. 2023MotionGPT: Finetuned LLMs Are General-Purpose Motion Generatorscited by 145
  14. 2023CG-HOI: Contact-Guided 3D Human-Object Interaction Generationcited by 138
  15. 2023TLControl: Trajectory and Language Control for Human Motion Synthesiscited by 94
  16. 2024Generating Human Interaction Motions in Scenes with Text Controlcited by 80
  17. 2024Flexible Motion In-betweening with Diffusion Modelscited by 71
  18. 2024MotionFix: Text-Driven 3D Human Motion Editingcited by 64
  19. 2024LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioningcited by 59
  20. 2023Breathing Life Into Sketches Using Text-to-Video Priorscited by 48
  21. 2023Iterative Motion Editing with Natural Languagecited by 40
  22. 2023MAS: Multi-view Ancestral Sampling for 3D motion generation using 2D diffusioncited by 37
  23. 2023Motion In-Betweening with Phase Manifoldscited by 25
  24. 2022GANimator: Neural Motion Synthesis from a Single Sequencecited by 23
  25. 2023A Method for Animating Children's Drawings of the Human Figurecited by 20
  26. 2024Lifting Motion to the 3D World via 2D Diffusioncited by 11
  27. 2024DrawingSpinUp: 3D Animation from Single Character Drawingscited by 9
  28. 2021Object Wake-up: 3D Object Rigging from a Single Imagecited by 8
  29. 2024Enhancing Sketch Animation: Text-to-Video Diffusion Models with Temporal Consistency and Rigidity Constraintscited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 9; 2026: 8.

17 papers.

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  1. 2026ProjFlow: Projection Sampling with Flow Matching for Zero-Shot Exact Spatial Motion Controlcited by 5
  2. 2025X-MoGen: Unified Motion Generation across Humans and Animalscited by 4
  3. 2026StoryBlender: Inter-Shot Consistent and Editable 3D Storyboard with Spatial-temporal Dynamicscited by 3
  4. 2026Sketch2Colab: Sketch-Conditioned Multi-Human Animation via Controllable Flow Distillationcited by 1
  5. 2026DancingBox: A Lightweight MoCap System for Character Animation from Physical Proxiescited by 1
  6. 2026Sketch2Motion: Text-driven 2D Sketch to 3D Animation via Diffusion-guided Skeleton Optimizationcited by 1
  7. 2025Deeply Dual Supervised learning for melanoma recognitioncited by 0
  8. 2025Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsamplingcited by 0
  9. 2025DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentationcited by 0
  10. 2025VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagationcited by 0
  11. 2025Generating Detailed Character Motion from Blocking Posescited by 0
  12. 2025REFINE-CONTROL: A Semi-supervised Distillation Method For Conditional Image Generationcited by 0
5 more
  1. 20254-Doodle: Text to 3D Sketches that Move!cited by 0
  2. 2025Pressure2Motion: Hierarchical Human Motion Reconstruction from Ground Pressure with Text Guidancecited by 0
  3. 2026A Self-Supervised Approach on Motion Calibration for Enhancing Physical Plausibility in Text-to-Motioncited by 0
  4. 2026Mat'ern Noise for Triangulation-Agnostic Flow Matching on Meshescited by 0
  5. 2026CleanMDM: Clean Motion Diffusion Model for Multimodal Motion Cleanupcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations
  2. 2026SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation Generation ↗
  3. 2026SketchKeyAnime: Reference-anchored Sparse Key-Sketch Animation Synthesis
  4. 2024Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
  5. 2025SketchAnimator: Animate Sketch via Motion Customization of Text-to-Video Diffusion Models
  6. 2025Sketch2PoseNet: Efficient and Generalized Sketch to 3D Human Pose Prediction
  7. 2024Sketch-Guided Stylized Landscape Cinemagraph Synthesis
  8. 2026VideoSketcher: Sequential Sketch Generation Using Video Model Priors