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Recent advancements in text-to-image models have significantly enhanced image generation capabilities, yet a notable gap of open-source models persists in bilingual or Chinese language support. To address this need, we present…

Computation and Language · Computer Science 2024-06-19 Xiaojun Wu , Dixiang Zhang , Ruyi Gan , Junyu Lu , Ziwei Wu , Renliang Sun , Jiaxing Zhang , Pingjian Zhang , Yan Song

Taking advantage of the many recent advances in deep learning, text-to-image generative models currently have the merit of attracting the general public attention. Two of these models, DALL-E 2 and Imagen, have demonstrated that highly…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Robin Zbinden

Diffusion models have made impressive progress in text-to-image synthesis. However, training such large-scale models (e.g. Stable Diffusion), from scratch requires high computational costs and massive high-quality text-image pairs, which…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Jinyi Hu , Xu Han , Xiaoyuan Yi , Yutong Chen , Wenhao Li , Zhiyuan Liu , Maosong Sun

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

Text-to-Image generation (TTI) technologies are advancing rapidly, especially in the English language communities. However, apart from the user input language barrier problem, English-native TTI models inherently carry biases from their…

Computation and Language · Computer Science 2026-03-19 Shanyuan Liu , Bo Cheng , Yuhang Ma , Liebucha Wu , Ao Ma , Xiaoyu Wu , Dawei Leng , Yuhui Yin

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However, their reliance on substantial computational resources and…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Guansong Lu , Yuanfan Guo , Jianhua Han , Minzhe Niu , Yihan Zeng , Songcen Xu , Zeyi Huang , Zhao Zhong , Wei Zhang , Hang Xu

Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Narek Tumanyan , Michal Geyer , Shai Bagon , Tali Dekel

Generative artificial intelligence (AI) refers to algorithms that create synthetic but realistic output. Diffusion models currently offer state of the art performance in generative AI for images. They also form a key component in more…

Machine Learning · Computer Science 2023-12-27 Catherine F. Higham , Desmond J. Higham , Peter Grindrod

Recent progress in text-to-image (TTI) systems, such as StableDiffusion, Imagen, and DALL-E 2, have made it possible to create realistic images with simple text prompts. It is tempting to use these systems to eliminate the manual task of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 David Marwood , Shumeet Baluja , Yair Alon

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

Recent progress in generative AI, especially diffusion models, has demonstrated significant utility in text-to-image synthesis. Particularly in healthcare, these models offer immense potential in generating synthetic datasets and training…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yan Luo , Muhammad Osama Khan , Congcong Wen , Muhammad Muneeb Afzal , Titus Fidelis Wuermeling , Min Shi , Yu Tian , Yi Fang , Mengyu Wang

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

We do not pursue a novel method in this paper, but aim to study if a modern text-to-image diffusion model can tailor any task-adaptive image classifier across domains and categories. Existing domain adaptive image classification works…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Weijie Chen , Haoyu Wang , Shicai Yang , Lei Zhang , Wei Wei , Yanning Zhang , Luojun Lin , Di Xie , Yueting Zhuang

We proposed the Chinese Text Adapter-Flux (CTA-Flux). An adaptation method fits the Chinese text inputs to Flux, a powerful text-to-image (TTI) generative model initially trained on the English corpus. Despite the notable image generation…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Yue Gong , Shanyuan Liu , Liuzhuozheng Li , Jian Zhu , Bo Cheng , Liebucha Wu , Xiaoyu Wu , Yuhang Ma , Dawei Leng , Yuhui Yin

Text-to-image diffusion models are well-known for their ability to generate realistic images based on textual prompts. However, the existing works have predominantly focused on English, lacking support for non-English text-to-image models.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Jian Ma , Chen Chen , Qingsong Xie , Haonan Lu

Thanks to the rapid development of diffusion models, unprecedented progress has been witnessed in image synthesis. Prior works mostly rely on pre-trained linguistic models, but a text is often too abstract to properly specify all the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Binbin Yang , Yi Luo , Ziliang Chen , Guangrun Wang , Xiaodan Liang , Liang Lin

Recently, large-scale text-to-image (T2I) diffusion models have emerged as a powerful tool for image-to-image translation (I2I), allowing open-domain image translation via user-provided text prompts. This paper proposes frequency-controlled…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Xiang Gao , Zhengbo Xu , Junhan Zhao , Jiaying Liu

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

Large Text-to-Image(T2I) diffusion models have shown a remarkable capability to produce photorealistic and diverse images based on text inputs. However, existing works only support limited language input, e.g., English, Chinese, and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-24 Fulong Ye , Guang Liu , Xinya Wu , Ledell Wu
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