Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training
We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on part-aware optimization, manual assembly, or 2D image generation, often produce unrealistic or incoherent 3D assets due to the challenges of intricate part-level manipulation and limited out-of-domain generation. In contrast, Muses leverages the 3D skeleton, a fundamental representation of biological forms, to explicitly and rationally compose diverse elements. This skeletal foundation formalizes 3D content creation as a structure-aware pipeline of design, composition, and generation. Muses begins by constructing a creatively composed 3D skeleton with coherent layout and scale through graph-constrained reasoning. This skeleton then guides a voxel-based assembly process within a structured latent space, integrating regions from different objects. Finally, image-guided appearance modeling under skeletal conditions is applied to generate a style-consistent and harmonious texture for the assembled shape. Extensive experiments establish Muses' state-of-the-art performance in terms of visual fidelity and alignment with textual descriptions, and potential on flexible 3D object editing. Project page: https://luhexiao.github.io/Muses.github.io/.
695dd790c03d6d81e4399f93
Hexiao Lu
claimed_verified
2026-01-07T09:25:41.192Z
66a4a7d02f869fd1e8a608e7
https://cdn-avatars.huggingface.co/v1/production/uploads/66a4a7d02f869fd1e8a608e7/ibcoHxegtjL42bY7io8CL.png
Hexiao Lu
CraneLu
user
CraneLu
695dd790c03d6d81e4399f94
Xiaokun Sun
admin_assigned
2026-01-07T13:38:09.493Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/65813fbeabafd960c84fdf2f/-2YSyWi8M3hZC2V_Qcss5.png
Xiaokun Sun
XiaokunSun
user
XiaokunSun
695dd790c03d6d81e4399f95
Zeyu Cai
695dd790c03d6d81e4399f96
Hao Guo
695dd790c03d6d81e4399f97
Ying Tai
695dd790c03d6d81e4399f98
Jian Yang
695dd790c03d6d81e4399f99
Zhenyu Zhang
Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training
We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on part-aware optimization, manual assembly, or 2D image generation, often produce unrealistic or incoherent 3D assets due to the challenges of intricate part-level manipulation and limited out-of-domain generation. In contrast, Muses leverages the 3D skeleton, a fundamental representation of biological forms, to explicitly and rationally compose diverse elements. This skeletal foundation formalizes 3D content creation as a structure-aware pipeline of design, composition, and generation. Muses begins by constructing a creatively composed 3D skeleton with coherent layout and scale through graph-constrained reasoning. This skeleton then guides a voxel-based assembly process within a structured latent space, integrating regions from different objects. Finally, image-guided appearance modeling under skeletal conditions is applied to generate a style-consistent and harmonious texture for the assembled shape. Extensive experiments establish Muses' state-of-the-art performance in terms of visual fidelity and alignment with textual descriptions, and potential on flexible 3D object editing. Project page: https://luhexiao.github.io/Muses.github.io/.
Muses enables feed-forward generation of 3D creatures by leveraging skeletal structures and graph-constrained reasoning for coherent design and assembly.
3D creature generation 3D skeleton graph-constrained reasoning voxel-based assembly structured latent space image-guided appearance modeling skeletal conditions