mlsanityData to 7 Oct 2026

Sprite Sheet Diffusion: Generate Game Character for Animation

arXiv 2412.03685 ↗First posted 4 Dec 2024cs.GR cs.CVcited by 1

On the map: Diffusion models → Video generation

Abstract (arXiv)

In the game development process, creating character animations is a vital step that involves several stages. Typically for 2D games, illustrators begin by designing the main character image, which serves as the foundation for all subsequent animations. To create a smooth motion sequence, these subsequent animations involve drawing the character in different poses and actions, such as running, jumping, or attacking. This process requires significant manual effort from illustrators, as they must meticulously ensure consistency in design, proportions, and style across multiple motion frames. Each frame is drawn individually, making this a time-consuming and labor-intensive task. Generative models, such as diffusion models, have the potential to revolutionize this process by automating the creation of sprite sheets. Diffusion models, known for their ability to generate diverse images, can be adapted to create character animations. By leveraging the capabilities of diffusion models, we can significantly reduce the manual workload for illustrators, accelerate the animation creation process, and open up new creative possibilities in game development.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Video generation, one of 14 directions in Diffusion models. Builds on 13 of its 16 references that are in the map. First posted on arXiv 4 Dec 2024.

Builds on

13 of 16 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation28 Nov

Other references · 12

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  5. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
  6. 2023VBench: Comprehensive Benchmark Suite for Video Generative Modelscited by 1,755
  7. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,439
  8. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  9. 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
  10. 2020Deep Learning-Based Human Pose Estimation: A Surveycited by 205
  11. 2024AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animationcited by 191
  12. 2021Transfer Learning for Pose Estimation of Illustrated Characterscited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2025Text-to-Level Diffusion Models With Various Text Encoders for Super Mario Bros
  2. 2024Structured Pattern Expansion with Diffusion Models
  3. 2025From Rigging to Waving: 3D-Guided Diffusion for Natural Animation of Hand-Drawn Characters
  4. 2023State of the Art on Diffusion Models for Visual Computing
  5. 2025Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions
  6. 2024Taming Diffusion Probabilistic Models for Character Control
  7. 2024Towards motion from video diffusion models
  8. 2023AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models