_version_ 1866913350521192448
author Li, Zhimin
Zhang, Jianwei
Lin, Qin
Xiong, Jiangfeng
Long, Yanxin
Deng, Xinchi
Zhang, Yingfang
Liu, Xingchao
Huang, Minbin
Xiao, Zedong
Chen, Dayou
He, Jiajun
Li, Jiahao
Li, Wenyue
Zhang, Chen
Quan, Rongwei
Lu, Jianxiang
Huang, Jiabin
Yuan, Xiaoyan
Zheng, Xiaoxiao
Li, Yixuan
Zhang, Jihong
Zhang, Chao
Chen, Meng
Liu, Jie
Fang, Zheng
Wang, Weiyan
Xue, Jinbao
Tao, Yangyu
Zhu, Jianchen
Liu, Kai
Lin, Sihuan
Sun, Yifu
Li, Yun
Wang, Dongdong
Chen, Mingtao
Hu, Zhichao
Xiao, Xiao
Chen, Yan
Liu, Yuhong
Liu, Wei
Wang, Di
Yang, Yong
Jiang, Jie
Lu, Qinglin
author_facet Li, Zhimin
Zhang, Jianwei
Lin, Qin
Xiong, Jiangfeng
Long, Yanxin
Deng, Xinchi
Zhang, Yingfang
Liu, Xingchao
Huang, Minbin
Xiao, Zedong
Chen, Dayou
He, Jiajun
Li, Jiahao
Li, Wenyue
Zhang, Chen
Quan, Rongwei
Lu, Jianxiang
Huang, Jiabin
Yuan, Xiaoyan
Zheng, Xiaoxiao
Li, Yixuan
Zhang, Jihong
Zhang, Chao
Chen, Meng
Liu, Jie
Fang, Zheng
Wang, Weiyan
Xue, Jinbao
Tao, Yangyu
Zhu, Jianchen
Liu, Kai
Lin, Sihuan
Sun, Yifu
Li, Yun
Wang, Dongdong
Chen, Mingtao
Hu, Zhichao
Xiao, Xiao
Chen, Yan
Liu, Yuhong
Liu, Wei
Wang, Di
Yang, Yong
Jiang, Jie
Lu, Qinglin
contents We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transformer structure, text encoder, and positional encoding. We also build from scratch a whole data pipeline to update and evaluate data for iterative model optimization. For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images. Finally, Hunyuan-DiT can perform multi-turn multimodal dialogue with users, generating and refining images according to the context. Through our holistic human evaluation protocol with more than 50 professional human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image generation compared with other open-source models. Code and pretrained models are publicly available at github.com/Tencent/HunyuanDiT
format Preprint
id arxiv_https___arxiv_org_abs_2405_08748
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Li, Zhimin
Zhang, Jianwei
Lin, Qin
Xiong, Jiangfeng
Long, Yanxin
Deng, Xinchi
Zhang, Yingfang
Liu, Xingchao
Huang, Minbin
Xiao, Zedong
Chen, Dayou
He, Jiajun
Li, Jiahao
Li, Wenyue
Zhang, Chen
Quan, Rongwei
Lu, Jianxiang
Huang, Jiabin
Yuan, Xiaoyan
Zheng, Xiaoxiao
Li, Yixuan
Zhang, Jihong
Zhang, Chao
Chen, Meng
Liu, Jie
Fang, Zheng
Wang, Weiyan
Xue, Jinbao
Tao, Yangyu
Zhu, Jianchen
Liu, Kai
Lin, Sihuan
Sun, Yifu
Li, Yun
Wang, Dongdong
Chen, Mingtao
Hu, Zhichao
Xiao, Xiao
Chen, Yan
Liu, Yuhong
Liu, Wei
Wang, Di
Yang, Yong
Jiang, Jie
Lu, Qinglin
Computer Vision and Pattern Recognition
We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transformer structure, text encoder, and positional encoding. We also build from scratch a whole data pipeline to update and evaluate data for iterative model optimization. For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images. Finally, Hunyuan-DiT can perform multi-turn multimodal dialogue with users, generating and refining images according to the context. Through our holistic human evaluation protocol with more than 50 professional human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image generation compared with other open-source models. Code and pretrained models are publicly available at github.com/Tencent/HunyuanDiT
title Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2405.08748