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DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation

Weizhe Liu, Yunjie Wu, Xiangqian Shu, Guangwei Wang, Xiangyu Xu, Peng Li, Yujie Li, Hengkai Guo

arXiv:2607.07817Published July 8, 20260 citations
  • cs.CV
  • cs.AI
  • foundation model

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.

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