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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2509.12815 |
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| _version_ | 1866909791200215040 |
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| author | Lei, Biwen Li, Yang Liu, Xinhai Yang, Shuhui Xu, Lixin Huang, Jingwei Tang, Ruining Weng, Haohan Liu, Jian Xu, Jing Zhou, Zhen Zhu, Yiling Xing, Jiankai Xu, Jiachen Ma, Changfeng Yan, Xinhao Yang, Yunhan Wang, Chunshi Xu, Duoteng Ma, Xueqi Chen, Yuguang Li, Jing Yang, Mingxin Zhang, Sheng Feng, Yifei Huang, Xin Luo, Di He, Zebin Jiang, Puhua Hu, Changrong Qin, Zihan Miao, Shiwei Liu, Haolin Zhao, Yunfei Lai, Zeqiang Lin, Qingxiang Zhao, Zibo Li, Kunhong Yang, Xianghui Shi, Huiwen Yang, Xin Wang, Yuxuan Yao, Zebin Lian, Yihang Liu, Sicong Han, Xintong Qin, Wangchen Ouyang, Caisheng Liu, Jianyin Yuan, Tianwen Jiang, Shuai Duan, Hong Niu, Yanqi Lin, Wencong Sun, Yifu Huang, Shirui Niu, Lin Gong, Gu Xiao, Guojian Zheng, Bojian Yuan, Xiang Chen, Qi Xiao, Jie Zheng, Dongyang Yang, Xiaofeng Liu, Kai Zhu, Jianchen Wang, Lifu Lu, Qinglin Liu, Jie Dong, Liang Jiang, Fan Chen, Ruibin Wang, Lei Zhang, Chao Lin, Jiaxin Zhang, Hao Ye, Zheng He, Peng Wu, Runzhou Wu, Yinhe Du, Jiayao Chen, Jupeng Mao, Xinyue Guo, Dongyuan Tang, Yixuan Tsai, Yulin Tan, Yonghao Yu, Jiaao Yu, Junlin Zhang, Keren Li, Yifan Chen, Peng Liu, Tian Wang, Di Liu, Yuhong Linus Jiang, Jie Chen, Zhuo Guo, Chunchao |
| author_facet | Lei, Biwen Li, Yang Liu, Xinhai Yang, Shuhui Xu, Lixin Huang, Jingwei Tang, Ruining Weng, Haohan Liu, Jian Xu, Jing Zhou, Zhen Zhu, Yiling Xing, Jiankai Xu, Jiachen Ma, Changfeng Yan, Xinhao Yang, Yunhan Wang, Chunshi Xu, Duoteng Ma, Xueqi Chen, Yuguang Li, Jing Yang, Mingxin Zhang, Sheng Feng, Yifei Huang, Xin Luo, Di He, Zebin Jiang, Puhua Hu, Changrong Qin, Zihan Miao, Shiwei Liu, Haolin Zhao, Yunfei Lai, Zeqiang Lin, Qingxiang Zhao, Zibo Li, Kunhong Yang, Xianghui Shi, Huiwen Yang, Xin Wang, Yuxuan Yao, Zebin Lian, Yihang Liu, Sicong Han, Xintong Qin, Wangchen Ouyang, Caisheng Liu, Jianyin Yuan, Tianwen Jiang, Shuai Duan, Hong Niu, Yanqi Lin, Wencong Sun, Yifu Huang, Shirui Niu, Lin Gong, Gu Xiao, Guojian Zheng, Bojian Yuan, Xiang Chen, Qi Xiao, Jie Zheng, Dongyang Yang, Xiaofeng Liu, Kai Zhu, Jianchen Wang, Lifu Lu, Qinglin Liu, Jie Dong, Liang Jiang, Fan Chen, Ruibin Wang, Lei Zhang, Chao Lin, Jiaxin Zhang, Hao Ye, Zheng He, Peng Wu, Runzhou Wu, Yinhe Du, Jiayao Chen, Jupeng Mao, Xinyue Guo, Dongyuan Tang, Yixuan Tsai, Yulin Tan, Yonghao Yu, Jiaao Yu, Junlin Zhang, Keren Li, Yifan Chen, Peng Liu, Tian Wang, Di Liu, Yuhong Linus Jiang, Jie Chen, Zhuo Guo, Chunchao |
| contents | The creation of high-quality 3D assets, a cornerstone of modern game development, has long been characterized by labor-intensive and specialized workflows. This paper presents Hunyuan3D Studio, an end-to-end AI-powered content creation platform designed to revolutionize the game production pipeline by automating and streamlining the generation of game-ready 3D assets. At its core, Hunyuan3D Studio integrates a suite of advanced neural modules (such as Part-level 3D Generation, Polygon Generation, Semantic UV, etc.) into a cohesive and user-friendly system. This unified framework allows for the rapid transformation of a single concept image or textual description into a fully-realized, production-quality 3D model complete with optimized geometry and high-fidelity PBR textures. We demonstrate that assets generated by Hunyuan3D Studio are not only visually compelling but also adhere to the stringent technical requirements of contemporary game engines, significantly reducing iteration time and lowering the barrier to entry for 3D content creation. By providing a seamless bridge from creative intent to technical asset, Hunyuan3D Studio represents a significant leap forward for AI-assisted workflows in game development and interactive media. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_12815 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hunyuan3D Studio: End-to-End AI Pipeline for Game-Ready 3D Asset Generation Lei, Biwen Li, Yang Liu, Xinhai Yang, Shuhui Xu, Lixin Huang, Jingwei Tang, Ruining Weng, Haohan Liu, Jian Xu, Jing Zhou, Zhen Zhu, Yiling Xing, Jiankai Xu, Jiachen Ma, Changfeng Yan, Xinhao Yang, Yunhan Wang, Chunshi Xu, Duoteng Ma, Xueqi Chen, Yuguang Li, Jing Yang, Mingxin Zhang, Sheng Feng, Yifei Huang, Xin Luo, Di He, Zebin Jiang, Puhua Hu, Changrong Qin, Zihan Miao, Shiwei Liu, Haolin Zhao, Yunfei Lai, Zeqiang Lin, Qingxiang Zhao, Zibo Li, Kunhong Yang, Xianghui Shi, Huiwen Yang, Xin Wang, Yuxuan Yao, Zebin Lian, Yihang Liu, Sicong Han, Xintong Qin, Wangchen Ouyang, Caisheng Liu, Jianyin Yuan, Tianwen Jiang, Shuai Duan, Hong Niu, Yanqi Lin, Wencong Sun, Yifu Huang, Shirui Niu, Lin Gong, Gu Xiao, Guojian Zheng, Bojian Yuan, Xiang Chen, Qi Xiao, Jie Zheng, Dongyang Yang, Xiaofeng Liu, Kai Zhu, Jianchen Wang, Lifu Lu, Qinglin Liu, Jie Dong, Liang Jiang, Fan Chen, Ruibin Wang, Lei Zhang, Chao Lin, Jiaxin Zhang, Hao Ye, Zheng He, Peng Wu, Runzhou Wu, Yinhe Du, Jiayao Chen, Jupeng Mao, Xinyue Guo, Dongyuan Tang, Yixuan Tsai, Yulin Tan, Yonghao Yu, Jiaao Yu, Junlin Zhang, Keren Li, Yifan Chen, Peng Liu, Tian Wang, Di Liu, Yuhong Linus Jiang, Jie Chen, Zhuo Guo, Chunchao Computer Vision and Pattern Recognition The creation of high-quality 3D assets, a cornerstone of modern game development, has long been characterized by labor-intensive and specialized workflows. This paper presents Hunyuan3D Studio, an end-to-end AI-powered content creation platform designed to revolutionize the game production pipeline by automating and streamlining the generation of game-ready 3D assets. At its core, Hunyuan3D Studio integrates a suite of advanced neural modules (such as Part-level 3D Generation, Polygon Generation, Semantic UV, etc.) into a cohesive and user-friendly system. This unified framework allows for the rapid transformation of a single concept image or textual description into a fully-realized, production-quality 3D model complete with optimized geometry and high-fidelity PBR textures. We demonstrate that assets generated by Hunyuan3D Studio are not only visually compelling but also adhere to the stringent technical requirements of contemporary game engines, significantly reducing iteration time and lowering the barrier to entry for 3D content creation. By providing a seamless bridge from creative intent to technical asset, Hunyuan3D Studio represents a significant leap forward for AI-assisted workflows in game development and interactive media. |
| title | Hunyuan3D Studio: End-to-End AI Pipeline for Game-Ready 3D Asset Generation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.12815 |