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This study focuses on a novel task in text-to-image (T2I) generation, namely action customization. The objective of this task is to learn the co-existing action from limited data and generalize it to unseen humans or even animals.…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Siteng Huang , Biao Gong , Yutong Feng , Xi Chen , Yuqian Fu , Yu Liu , Donglin Wang

Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusion models gradually synthesize images in an iterative fashion…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Yogesh Balaji , Seungjun Nah , Xun Huang , Arash Vahdat , Jiaming Song , Qinsheng Zhang , Karsten Kreis , Miika Aittala , Timo Aila , Samuli Laine , Bryan Catanzaro , Tero Karras , Ming-Yu Liu

Text-to-image generative models have recently garnered significant attention due to their ability to generate images based on prompt descriptions. While these models have shown promising performance, concerns have been raised regarding the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Meiling Li , Zhenxing Qian , Xinpeng Zhang

The ability to synthesize personalized group photos and specify the positions of each identity offers immense creative potential. While such imagery can be visually appealing, it presents significant challenges for existing technologies. A…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yimeng Zhang , Tiancheng Zhi , Jing Liu , Shen Sang , Liming Jiang , Qing Yan , Sijia Liu , Linjie Luo

Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts. Such text-based synthesis methods are particularly…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Amir Hertz , Ron Mokady , Jay Tenenbaum , Kfir Aberman , Yael Pritch , Daniel Cohen-Or

Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt. However, these models lack the ability to mimic the appearance of subjects in a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Nataniel Ruiz , Yuanzhen Li , Varun Jampani , Yael Pritch , Michael Rubinstein , Kfir Aberman

Text-driven image manipulation remains challenging in training or inference flexibility. Conditional generative models depend heavily on expensive annotated training data. Meanwhile, recent frameworks, which leverage pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Yueming Lyu , Tianwei Lin , Fu Li , Dongliang He , Jing Dong , Tieniu Tan

Text-to-Face (TTF) synthesis is a challenging task with great potential for diverse computer vision applications. Compared to Text-to-Image (TTI) synthesis tasks, the textual description of faces can be much more complicated and detailed…

Computer Vision and Pattern Recognition · Computer Science 2020-09-21 Tianren Wang , Teng Zhang , Brian Lovell

Recent advances in large pretrained text-to-image models have shown unprecedented capabilities for high-quality human-centric generation, however, customizing face identity is still an intractable problem. Existing methods cannot ensure…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Qinghe Wang , Xu Jia , Xiaomin Li , Taiqing Li , Liqian Ma , Yunzhi Zhuge , Huchuan Lu

Recent advances in text-to-image (T2I) generation have led to impressive visual results. However, these models still face significant challenges when handling complex prompt, particularly those involving multiple subjects with distinct…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Lifeng Chen , Jiner Wang , Zihao Pan , Beier Zhu , Xiaofeng Yang , Chi Zhang

Generative models have been widely studied in computer vision. Recently, diffusion models have drawn substantial attention due to the high quality of their generated images. A key desired property of image generative models is the ability…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Qiucheng Wu , Yujian Liu , Handong Zhao , Ajinkya Kale , Trung Bui , Tong Yu , Zhe Lin , Yang Zhang , Shiyu Chang

Text-to-Image (T2I) diffusion models have recently gained traction for their versatility and user-friendliness in 2D content generation and editing. However, training a diffusion model specifically for 3D scene editing is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Nazmul Karim , Hasan Iqbal , Umar Khalid , Jing Hua , Chen Chen

Customization of text-to-image models enables users to insert new concepts or objects and generate them in unseen settings. Existing methods either rely on comparatively expensive test-time optimization or train encoders on single-image…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Nupur Kumari , Xi Yin , Jun-Yan Zhu , Ishan Misra , Samaneh Azadi

Recent advances in diffusion models (DMs) have achieved exceptional visual quality in image editing tasks. However, the global denoising dynamics of DMs inherently conflate local editing targets with the full-image context, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Wei Chow , Linfeng Li , Lingdong Kong , Zefeng Li , Qi Xu , Hang Song , Tian Ye , Xian Wang , Jinbin Bai , Shilin Xu , Xiangtai Li , Junting Pan , Shaoteng Liu , Ran Zhou , Tianshu Yang , Songhua Liu

Text-to-image generation models have seen considerable advancement, catering to the increasing interest in personalized image creation. Current customization techniques often necessitate users to provide multiple images (typically 3-5) for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Linhao Zhong , Yan Hong , Wentao Chen , Binglin Zhou , Yiyi Zhang , Jianfu Zhang , Liqing Zhang

Text-guided image-to-image diffusion models excel in translating images based on textual prompts, allowing for precise and creative visual modifications. However, such a powerful technique can be misused for spreading misinformation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Wenhao Wang , Yifan Sun , Zongxin Yang , Zhentao Tan , Zhengdong Hu , Yi Yang

The recent large-scale generative modeling has attained unprecedented performance especially in producing high-fidelity images driven by text prompts. Text inversion (TI), alongside the text-to-image model backbones, is proposed as an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Jianan Yang , Haobo Wang , Yanming Zhang , Ruixuan Xiao , Sai Wu , Gang Chen , Junbo Zhao

Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on specific text prompts. However, existing T2I-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Salaheldin Mohamed , Dong Han , Yong Li

With the great success of text-conditioned diffusion models in creative text-to-image generation, various text-driven image editing approaches have attracted the attentions of many researchers. However, previous works mainly focus on…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zhiyuan Ma , Guoli Jia , Bowen Zhou

Image-to-image translation is to convert an image of the certain style to another of the target style with the content preserved. A desired translator should be capable to generate diverse results in a controllable (many-to-many) fashion.…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Yuanbin Fu , Jiayi Ma , Lin Ma , Xiaojie Guo
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