DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
This work addresses the need for production-ready 3D character generation, offering a practical post-adaptation framework for industry use.
DreamCharacter-1 adapts pretrained 3D foundation models for high-fidelity 3D character generation, achieving state-of-the-art results in visual quality and structural robustness.
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.