1 citations · 3 across the 5 of their papers we have counts for
6 papers
HY3D-Bench: Generation of 3D Assets
Team Hunyuan3D, :, Bowen Zhang +22
While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlene…
Hunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assets
Team Hunyuan3D, :, Bowen Zhang +17
Recent advances in 3D-native generative models have accelerated asset creation for games, film, and design. However, most methods still rely primarily on image or text conditioning…
Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate Details
Zeqiang Lai, Yunfei Zhao, Haolin Liu +23
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…
Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material
Team Hunyuan3D, Shuhui Yang, Mingxin Yang +50
3D AI-generated content (AIGC) is a passionate field that has significantly accelerated the creation of 3D models in gaming, film, and design. Despite the development of several gr…
Unleashing Vecset Diffusion Model for Fast Shape Generation
Zeqiang Lai, Yunfei Zhao, Zibo Zhao +10
3D shape generation has greatly flourished through the development of so-called "native" 3D diffusion, particularly through the Vecset Diffusion Model (VDM). While recent advanceme…
Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation
Xianghui Yang, Huiwen Shi, Bowen Zhang +20
While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address…