Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate
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Authors: name: Zeqiang Lai, name: Yunfei Zhao, name: Haolin Liu, name: Zibo Zhao, name: Qingxiang Lin, name: Huiwen Shi, name: Xianghui Yang, name: Mingxin Yang, name: Shuhui Yang, name: Yifei Feng, name: Sheng Zhang, name: Xin Huang, name: Di Luo, name: Fan Yang, name: Fang Yang, name: Lifu Wang, name: Sicong Liu, name: Yixuan Tang, name: Yulin Cai, name: Zebin He, name: Tian Liu, name: Yuhong Liu, name: Jie Jiang, name: Linus, name: Jingwei Huang, name: Chunchao Guo

In this report, we present Hunyuan3D 2.5, a robust suite of 3D diffusion
models aimed at generating high-fidelity and detailed textured 3D assets.
Hunyuan3D 2.5 follows two-stages pipeline of its previous version Hunyuan3D
2.0, while demonstrating substantial advancements in both shape and texture
generation. In terms of shape generation, we introduce a new shape foundation
model -- LATTICE, which is trained with scaled high-quality datasets,
model-size, and compute. Our largest model reaches 10B parameters and generates
sharp and detailed 3D shape with precise image-3D following while keeping mesh
surface clean and smooth, significantly closing the gap between generated and
handcrafted 3D shapes. In terms of texture generation, it is upgraded with
phyiscal-based rendering (PBR) via a novel multi-view architecture extended
from Hunyuan3D 2.0 Paint model. Our extensive evaluation shows that Hunyuan3D
2.5 significantly outperforms previous methods in both shape and end-to-end
texture generation.