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Recent text-to-image generative models have enabled us to transform our words into vibrant, captivating imagery. The surge of personalization techniques that has followed has also allowed us to imagine unique concepts in new scenes.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Elad Richardson , Kfir Goldberg , Yuval Alaluf , Daniel Cohen-Or

We introduce a method for composing object-level visual prompts within a text-to-image diffusion model. Our approach addresses the task of generating semantically coherent compositions across diverse scenes and styles, similar to the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Gaurav Parmar , Or Patashnik , Kuan-Chieh Wang , Daniil Ostashev , Srinivasa Narasimhan , Jun-Yan Zhu , Daniel Cohen-Or , Kfir Aberman

In recent years, multi-concept personalization for text-to-image (T2I) diffusion models to represent several subjects in an image has gained much more attention. The main challenge of this task is "concept mixing", where multiple learned…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Habin Lim , Yeongseob Won , Juwon Seo , Gyeong-Moon Park

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-to-image diffusion models have emerged as powerful tools for high-quality image generation and editing. Many existing approaches rely on text prompts as editing guidance. However, these methods are constrained by the need for manual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Yuanyuan Chang , Yinghua Yao , Tao Qin , Mengmeng Wang , Ivor Tsang , Guang Dai

Text-to-image diffusion models have shown an impressive ability to generate high-quality images from input textual descriptions. However, concerns have been raised about the potential for these models to create content that infringes on…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Tingxu Han , Weisong Sun , Yanrong Hu , Chunrong Fang , Yonglong Zhang , Shiqing Ma , Tao Zheng , Zhenyu Chen , Zhenting Wang

Personalized image synthesis has emerged as a pivotal application in text-to-image generation, enabling the creation of images featuring specific subjects in diverse contexts. While diffusion models have dominated this domain,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Kaiyue Sun , Xian Liu , Yao Teng , Xihui Liu

We tackle the common challenge of inter-concept visual confusion in compositional concept generation using text-guided diffusion models (TGDMs). It becomes even more pronounced in the generation of customized concepts, due to the scarcity…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Wang Lin , Jingyuan Chen , Jiaxin Shi , Yichen Zhu , Chen Liang , Junzhong Miao , Tao Jin , Zhou Zhao , Fei Wu , Shuicheng Yan , Hanwang Zhang

Textual image generation spans diverse fields like advertising, education, product packaging, social media, information visualization, and branding. Despite recent strides in language-guided image synthesis using diffusion models, current…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Shubham Paliwal , Arushi Jain , Monika Sharma , Vikram Jamwal , Lovekesh Vig

Visual concept learning, also known as Text-to-image personalization, is the process of teaching new concepts to a pretrained model. This has numerous applications from product placement to entertainment and personalized design. Here we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Ori Malca , Dvir Samuel , Gal Chechik

Customizing pre-trained text-to-image generation model has attracted massive research interest recently, due to its huge potential in real-world applications. Although existing methods are able to generate creative content for a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yufan Zhou , Ruiyi Zhang , Jiuxiang Gu , Tong Sun

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

The quality of the prompts provided to text-to-image diffusion models determines how faithful the generated content is to the user's intent, often requiring `prompt engineering'. To harness visual concepts from target images without prompt…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Shweta Mahajan , Tanzila Rahman , Kwang Moo Yi , Leonid Sigal

Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain. However, expressing unique characteristics of an artwork (e.g. brushwork, colortone, or composition)…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Namhyuk Ahn , Junsoo Lee , Chunggi Lee , Kunhee Kim , Daesik Kim , Seung-Hun Nam , Kibeom Hong

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

Advanced image fusion methods are devoted to generating the fusion results by aggregating the complementary information conveyed by the source images. However, the difference in the source-specific manifestation of the imaged scene content…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Chunyang Cheng , Tianyang Xu , Xiao-Jun Wu , Hui Li , Xi Li , Zhangyong Tang , Josef Kittler

Text-to-image models offer unprecedented freedom to guide creation through natural language. Yet, it is unclear how such freedom can be exercised to generate images of specific unique concepts, modify their appearance, or compose them in…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Rinon Gal , Yuval Alaluf , Yuval Atzmon , Or Patashnik , Amit H. Bermano , Gal Chechik , Daniel Cohen-Or

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

Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process. Many practice designers use text-based searches on platforms like Pinterest to…

Human-Computer Interaction · Computer Science 2024-07-18 Ye Wang , Nicole B. Damen , Thomas Gale , Voho Seo , Hooman Shayani

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