mlsanityData to 7 Oct 2026

Make-A-Character: High Quality Text-to-3D Character Generation within Minutes

arXiv 2312.15430 ↗First posted 24 Dec 2023cs.CVcited by 8

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Abstract (arXiv)

There is a growing demand for customized and expressive 3D characters with the emergence of AI agents and Metaverse, but creating 3D characters using traditional computer graphics tools is a complex and time-consuming task. To address these challenges, we propose a user-friendly framework named Make-A-Character (Mach) to create lifelike 3D avatars from text descriptions. The framework leverages the power of large language and vision models for textual intention understanding and intermediate image generation, followed by a series of human-oriented visual perception and 3D generation modules. Our system offers an intuitive approach for users to craft controllable, realistic, fully-realized 3D characters that meet their expectations within 2 minutes, while also enabling easy integration with existing CG pipeline for dynamic expressiveness. For more information, please visit the project page at https://human3daigc.github.io/MACH/.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 12 of its 24 references that are in the map. First posted on arXiv 24 Dec 2023.

Builds on

12 of 24 references.

References · 12

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  4. 2023Qwen Technical Reportcited by 3,273
  5. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  6. 2019Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Setcited by 481
  7. 2020Learning an Animatable Detailed 3D Face Model from In-The-Wild Imagescited by 475
  8. 2020FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Predictioncited by 196
  9. 2018Look at Boundary: A Boundary-Aware Face Alignment Algorithmcited by 137
  10. 20223D face reconstruction with dense landmarkscited by 70
  11. 2023STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detectioncited by 41
  12. 2022NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representationscited by 31

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 4; 2026: 1.

8 papers.

  1. 2024GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splattingcited by 104
  2. 2024SceneTeller: Language-to-3D Scene Generationcited by 43
  3. 2024Large Language Models and Video Games: A Preliminary Scoping Reviewcited by 23
  4. 2025ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modelingcited by 12
  5. 2025MHR: Momentum Human Rigcited by 9
  6. 2025CartoonAlive: Towards Expressive Live2D Modeling from Single Portraitscited by 1
  7. 2026OmniFaceRig: Fully Automatic Inner-Mouth-Aware Face Rigging Across Diverse 3D Character Topologiescited by 1
  8. 20252K-Characters-10K-Stories: A Quality-Gated Stylized Narrative Dataset with Disentangled Control and Sequence Consistencycited by 0