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Despite advancements in text-to-image generation (T2I), prior methods often face text-image misalignment problems such as relation confusion in generated images. Existing solutions involve cross-attention manipulation for better…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Leigang Qu , Wenjie Wang , Yongqi Li , Hanwang Zhang , Liqiang Nie , Tat-Seng Chua

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

The popularization of Text-to-Image (T2I) diffusion models enables the generation of high-quality images from text descriptions. However, generating diverse customized images with reference visual attributes remains challenging. This work…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Brian Nlong Zhao , Yuhang Xiao , Jiashu Xu , Xinyang Jiang , Yifan Yang , Dongsheng Li , Laurent Itti , Vibhav Vineet , Yunhao Ge

Text-to-Image (T2I) models have recently achieved remarkable success in generating images from textual descriptions. However, challenges still persist in accurately rendering complex scenes where actions and interactions form the primary…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Vatsal Malaviya , Agneet Chatterjee , Maitreya Patel , Yezhou Yang , Chitta Baral

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

Text-to-Image (T2I) Diffusion Models have achieved remarkable performance in generating high quality images. However, enabling precise control of continuous attributes, especially multiple attributes simultaneously, in a new domain (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Wonwoong Cho , Yan-Ying Chen , Matthew Klenk , David I. Inouye , Yanxia Zhang

Text-to-Image (T2I) generation has made significant advancements with the advent of diffusion models. These models exhibit remarkable abilities to produce images based on textual prompts. Current T2I models allow users to specify object…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Muhammad Atif Butt , Kai Wang , Javier Vazquez-Corral , Joost van de Weijer

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing methods typically augment pretrained text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Xun Guo , Mingwu Zheng , Liang Hou , Yuan Gao , Yufan Deng , Pengfei Wan , Di Zhang , Yufan Liu , Weiming Hu , Zhengjun Zha , Haibin Huang , Chongyang Ma

Recently, pre-trained text-to-image (T2I) models have been extensively adopted for real-world image restoration because of their powerful generative prior. However, controlling these large models for image restoration usually requires a…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Junyuan Deng , Xinyi Wu , Yongxing Yang , Congchao Zhu , Song Wang , Zhenyao Wu

Ethical issues around text-to-image (T2I) models demand a comprehensive control over the generative content. Existing techniques addressing these issues for responsible T2I models aim for the generated content to be fair and safe…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Basim Azam , Naveed Akhtar

Image colorization has been attracting the research interests of the community for decades. However, existing methods still struggle to provide satisfactory colorized results given grayscale images due to a lack of human-like global…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Hanyuan Liu , Jinbo Xing , Minshan Xie , Chengze Li , Tien-Tsin Wong

Although text-to-image (T2I) models have recently thrived as visual generative priors, their reliance on high-quality text-image pairs makes scaling up expensive. We argue that grasping the cross-modality alignment is not a necessity for a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Shuailei Ma , Kecheng Zheng , Ying Wei , Wei Wu , Fan Lu , Yifei Zhang , Chen-Wei Xie , Biao Gong , Jiapeng Zhu , Yujun Shen

Text-to-image (T2I) generative models have gained increased popularity in the public domain. While boasting impressive user-guided generative abilities, their black-box nature exposes users to intentionally- and intrinsically-biased…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Jordan Vice , Naveed Akhtar , Richard Hartley , Ajmal Mian

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

Text-to-image (T2I) models are well known for their ability to produce highly realistic images, while multimodal large language models (MLLMs) are renowned for their proficiency in understanding and integrating multiple modalities. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jian Ma , Qirong Peng , Xu Guo , Chen Chen , Haonan Lu , Zhenyu Yang

Recent advancements in text-to-image (T2I) generative models have shown remarkable capabilities in producing diverse and imaginative visuals based on text prompts. Despite the advancement, these diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xiaohui Chen , Yongfei Liu , Yingxiang Yang , Jianbo Yuan , Quanzeng You , Li-Ping Liu , Hongxia Yang

Large-scale text-to-image (T2I) diffusion models have showcased incredible capabilities in generating coherent images based on textual descriptions, enabling vast applications in content generation. While recent advancements have introduced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiun Tian Hoe , Xudong Jiang , Chee Seng Chan , Yap-Peng Tan , Weipeng Hu

With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object…

Graphics · Computer Science 2025-08-13 Qianru Qiu , Jiafeng Mao , Xueting Wang

Recently, we have seen a surge of personalization methods for text-to-image (T2I) diffusion models to learn a concept using a few images. Existing approaches, when used for face personalization, suffer to achieve convincing inversion with…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Rishubh Parihar , Sachidanand VS , Sabariswaran Mani , Tejan Karmali , R. Venkatesh Babu
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