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20242026
most citedHunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assets

1 citations · 3 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV2026

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…

cs.CV20251 cited

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…

cs.CV20251 cited

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…

cs.CV20251 cited

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…

cs.GR2025

FreeMesh: Boosting Mesh Generation with Coordinates Merging

Jian Liu, Haohan Weng, Biwen Lei +6

The next-coordinate prediction paradigm has emerged as the de facto standard in current auto-regressive mesh generation methods. Despite their effectiveness, there is no efficient…

cs.CV2025

Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning

Jian Liu, Jing Xu, Song Guo +10

Existing pretrained models for 3D mesh generation often suffer from data biases and produce low-quality results, while global reinforcement learning (RL) methods rely on object-lev…