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
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Hunyuan-DiT, a text-to-image diffusion transformer, achieves state-of-the-art in Chinese-to-image generation by incorporating fine-grained language understanding and multi-turn dialogue capabilities.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 45
- Hosting
- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2405.08748ARXIV-DEFAULT
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- Semantic Scholar
Abstract
Authors
45Jie LiuJihong ZhangMeng ChenChao ZhangYifu SunYangyu TaoJianchen ZhuJinbao XueKai LiuDi WangYuhong LiuJie JiangJiahao LiJianwei ZhangYun LiZhichao HuYong YangXingchao LiuWei LiuZhimin LiQinglin LuChen ZhangYixuan LiQin LinXiao XiaoYan ChenZheng FangJiangfeng XiongYanxin LongWeiyan WangXinchi DengMingtao ChenXiaoyan YuanMinbin HuangJiajun HeYingfang ZhangZedong XiaoDayou ChenWenyue LiRongwei QuanJianxiang LuJiabin HuangXiaoxiao ZhengSihuan LinDongdong Wang