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Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Text-to-image diffusion models have recently taken center stage as pivotal tools in promoting visual creativity across an array of domains such as comic book artistry, children's literature, game development, and web design. These models…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Kiymet Akdemir , Pinar Yanardag

In text-to-image generation, producing a series of consistent contents that preserve the same identity is highly valuable for real-world applications. Although a few works have explored training-free methods to enhance the consistency of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Mengyu Wang , Henghui Ding , Jianing Peng , Yao Zhao , Yunpeng Chen , Yunchao Wei

Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject. Existing methods try to tackle this challenge and generate…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Jiahao Wang , Caixia Yan , Haonan Lin , Weizhan Zhang , Mengmeng Wang , Tieliang Gong , Guang Dai , Hao Sun

In text-to-image models, consistent character generation is the task of achieving text alignment while maintaining the subject's appearance across different prompts. However, since style and appearance are often entangled, the existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yohai Mazuz , Janna Bruner , Lior Wolf

The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components. While workflow-based approaches can lead to improved image quality, crafting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Rinon Gal , Adi Haviv , Yuval Alaluf , Amit H. Bermano , Daniel Cohen-Or , Gal Chechik

Generating a coherent sequence of images that tells a visual story, using text-to-image diffusion models, often faces the critical challenge of maintaining subject consistency across all story scenes. Existing approaches, which typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Gopalji Gaur , Mohammadreza Zolfaghari , Thomas Brox

The current state-of-the-art Diffusion model has demonstrated excellent results in generating images. However, the images are monotonous and are mostly the result of the distribution of images of people in the training set, making it…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Tianyu Chen

Personalized text-to-image generation has attracted unprecedented attention in the recent few years due to its unique capability of generating highly-personalized images via using the input concept dataset and novel textual prompt. However,…

Artificial Intelligence · Computer Science 2024-07-02 Shian Du , Xiaotian Cheng , Qi Qian , Henglu Wei , Yi Xu , Xiangyang Ji

Text-to-image models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models' sensitivity to human language nuances. With advancements…

Artificial Intelligence · Computer Science 2024-06-14 Xinrui Yang , Zhuohan Wang , Anthony Hu

Customized image generation, which seeks to synthesize images with consistent characters, holds significant relevance for applications such as storytelling, portrait generation, and character design. However, previous approaches have…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Yuhang Ma , Wenting Xu , Jiji Tang , Qinfeng Jin , Rongsheng Zhang , Zeng Zhao , Changjie Fan , Zhipeng Hu

Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yuxuan Zhang , Yiren Song , Jinpeng Yu , Han Pan , Zhongliang Jing

Well-designed prompts can guide text-to-image models to generate amazing images. However, the performant prompts are often model-specific and misaligned with user input. Instead of laborious human engineering, we propose prompt adaptation,…

Computation and Language · Computer Science 2024-01-01 Yaru Hao , Zewen Chi , Li Dong , Furu Wei

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

Generating high-fidelity images of humans with fine-grained control over attributes such as hairstyle and clothing remains a core challenge in personalized text-to-image synthesis. While prior methods emphasize identity preservation from a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Guocheng Gordon Qian , Daniil Ostashev , Egor Nemchinov , Avihay Assouline , Sergey Tulyakov , Kuan-Chieh Jackson Wang , Kfir Aberman

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Text-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language. However, using these models to consistently portray the same subject across diverse prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yoad Tewel , Omri Kaduri , Rinon Gal , Yoni Kasten , Lior Wolf , Gal Chechik , Yuval Atzmon

Large-scale text-to-image diffusion models have achieved great success in synthesizing high-quality and diverse images given target text prompts. Despite the revolutionary image generation ability, current state-of-the-art models still…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Jingyuan Zhu , Huimin Ma , Jiansheng Chen , Jian Yuan

Recent advancements in text-to-image generation using diffusion models have significantly improved the quality of generated images and expanded the ability to depict a wide range of objects. However, ensuring that these models adhere…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Michail Tarasiou , Stylianos Moschoglou , Jiankang Deng , Stefanos Zafeiriou
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