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

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arxiv 2312.15430 v1 pith:WLSYCL4N submitted 2023-12-24 cs.CV

classification cs.CV
keywords charactersgenerationframeworkmachmake-a-characterminutesaddressagents
verification ladder T0 review T1 audit T2 compute T3 formal
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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/.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modeling

    cs.CV 2025-08 conditional novelty 6.0 of 10

    ATLAS decouples skeleton and shape parameters in a parametric human body model, improving fit accuracy and controllability over previous models like SMPL-X.

  2. CartoonAlive: Towards Expressive Live2D Modeling from Single Portraits

    cs.CV 2025-07 conditional novelty 4.0 of 10

    CartoonAlive automatically generates an animatable Live2D cartoon character from a single portrait image by combining 3DMM-inspired blendshapes with landmark-guided parameter regression.

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