DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
DreamCharacter-1 is a lightweight post-adaptation framework that calibrates pretrained 3D foundation models for high-fidelity, production-ready 3D character generation. It includes geometry post-training, texture post-training, and inference acceleration, consistently outperforming state-of-the-art methods.
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[Submitted on 8 Jul 2026]
Title:DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
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Abstract:We present DreamCharacter-1, a lightweight post-adaptation framework that calibrates pretrained 3D foundation models toward high-fidelity, production-ready 3D character generation. Building upon a 3D foundation backbone, our pipeline incorporates three task-oriented components: (1) geometry post-training, which enhances fine-grained surface details through geometric preference optimization; (2) texture post-training, which synthesizes high-resolution textures and refines the appearance of occluded regions; and (3) inference acceleration, which enables scalable deployment. Extensive quantitative and qualitative experiments demonstrate that DreamCharacter-1 produces visually compelling and structurally robust 3D character assets, consistently surpassing state-of-the-art character generation methods.
Comments: Official Page: this https URL
Subjects:
Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI)
Cite as: arXiv:2607.07817 [cs.CV]
(or arXiv:2607.07817v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2607.07817
arXiv-issued DOI via DataCite (pending registration)
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From: Weizhe Liu [view email] [v1] Wed, 8 Jul 2026 18:02:57 UTC (44,340 KB)
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