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Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image generation is proceeding rather slowly. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jian Ma , Junhao Liang , Chen Chen , Haonan Lu

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Text-to-image (T2I) diffusion models, when fine-tuned on a few personal images, can generate visuals with a high degree of consistency. However, such fine-tuned models are not robust; they often fail to compose with concepts of pretrained…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Kyungmin Lee , Sangkyung Kwak , Kihyuk Sohn , Jinwoo Shin

Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images. Yet, the independent process of image generation in these prevailing methods leads to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Xianghui Yang , Yan Zuo , Sameera Ramasinghe , Loris Bazzani , Gil Avraham , Anton van den Hengel

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Pengcheng Xu , Qingnan Fan , Fei Kou , Shuai Qin , Hong Gu , Ruoyu Zhao , Charles Ling , Boyu Wang

Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Zijie Wu , Chaohui Yu , Zhen Zhu , Fan Wang , Xiang Bai

Text-to-image generative models have attracted rising attention for flexible image editing via user-specified descriptions. However, text descriptions alone are not enough to elaborate the details of subjects, often compromising the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Xin Zhang , Jiaxian Guo , Paul Yoo , Yutaka Matsuo , Yusuke Iwasawa

Recently, large-scale diffusion models, e.g., Stable diffusion and DallE2, have shown remarkable results on image synthesis. On the other hand, large-scale cross-modal pre-trained models (e.g., CLIP, ALIGN, and FILIP) are competent for…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Runhui Huang , Jianhua Han , Guansong Lu , Xiaodan Liang , Yihan Zeng , Wei Zhang , Hang Xu

Text-guided diffusion models have revolutionized generative tasks by producing high-fidelity content from text descriptions. They have also enabled an editing paradigm where concepts can be replaced through text conditioning (e.g., a dog to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Chao Huang , Susan Liang , Yunlong Tang , Yapeng Tian , Anurag Kumar , Chenliang Xu

Text-to-image generation models~(e.g., Stable Diffusion) have achieved significant advancements, enabling the creation of high-quality and realistic images based on textual descriptions. Prompt inversion, the task of identifying the textual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Mingzhe Li , Kejing Xia , Gehao Zhang , Zhenting Wang , Guanhong Tao , Siqi Pan , Juan Zhai , Shiqing Ma

Customized text-to-image generation, which synthesizes images based on user-specified concepts, has made significant progress in handling individual concepts. However, when extended to multiple concepts, existing methods often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiaxiu Jiang , Yabo Zhang , Kailai Feng , Xiaohe Wu , Wenbo Li , Renjing Pei , Fan Li , Wangmeng Zuo

Images generated by diffusion models like Stable Diffusion are increasingly widespread. Recent works and even lawsuits have shown that these models are prone to replicating their training data, unbeknownst to the user. In this paper, we…

Machine Learning · Computer Science 2023-06-01 Gowthami Somepalli , Vasu Singla , Micah Goldblum , Jonas Geiping , Tom Goldstein

Although diffusion models have demonstrated remarkable generative capabilities, existing style transfer techniques often struggle to maintain identity while achieving high-quality stylization. This limitation becomes particularly critical…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Mohammad Ali Rezaei , Helia Hajikazem , Saeed Khanehgir , Mahdi Javanmardi

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment. However, these models can also be misused to produce inappropriate content. Existing safety measures,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hongxiang Zhang , Yifeng He , Hao Chen

Text-to-image diffusion models excel at generating high-quality images from natural language descriptions but often fail to preserve subject consistency across multiple outputs, limiting their use in visual storytelling. Existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Shangxun Li , Youngjung Uh

Learning from feedback has been shown to enhance the alignment between text prompts and images in text-to-image diffusion models. However, due to the lack of focus in feedback content, especially regarding the object type and quantity,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Xuexiang Niu , Jinping Tang , Lei Wang , Ge Zhu

Recent advances in large-scale text-to-image models have revolutionized creative fields by generating visually captivating outputs from textual prompts; however, while traditional photography offers precise control over camera settings to…

Graphics · Computer Science 2025-06-17 Armando Fortes , Tianyi Wei , Shangchen Zhou , Xingang Pan

This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifically, the deep fusion of large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Bingda Tang , Boyang Zheng , Xichen Pan , Sayak Paul , Saining Xie

Text-to-image (T2I) customization aims to create images that embody specific visual concepts delineated in textual descriptions. However, existing works still face a main challenge, concept overfitting. To tackle this challenge, we first…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Weili Zeng , Yichao Yan , Qi Zhu , Zhuo Chen , Pengzhi Chu , Weiming Zhao , Xiaokang Yang