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Advanced diffusion-based Text-to-Image (T2I) models, such as the Stable Diffusion Model, have made significant progress in generating diverse and high-quality images using text prompts alone. However, when non-famous users require…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yang Li , Songlin Yang , Wei Wang , Jing Dong

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

Large-scale text-to-image diffusion models can generate high-fidelity images with powerful compositional ability. However, these models are typically trained on an enormous amount of Internet data, often containing copyrighted material,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Nupur Kumari , Bingliang Zhang , Sheng-Yu Wang , Eli Shechtman , Richard Zhang , Jun-Yan Zhu

Large-scale text-to-image diffusion models excel in generating high-quality images from textual inputs, yet concerns arise as research indicates their tendency to memorize and replicate training data, raising We also addressed the issue of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Ruchika Chavhan , Ondrej Bohdal , Yongshuo Zong , Da Li , Timothy Hospedales

Text-to-image generation has witnessed great progress, especially with the recent advancements in diffusion models. Since texts cannot provide detailed conditions like object appearance, reference images are usually leveraged for the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zhiqi Huang , Huixin Xiong , Haoyu Wang , Longguang Wang , Zhiheng Li

Cutting-edge diffusion models produce images with high quality and customizability, enabling them to be used for commercial art and graphic design purposes. But do diffusion models create unique works of art, or are they replicating content…

Machine Learning · Computer Science 2022-12-13 Gowthami Somepalli , Vasu Singla , Micah Goldblum , Jonas Geiping , Tom Goldstein

Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased. Existing safety methods typically refine prompts using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jinwoo Jeon , JunHyeok Oh , Hayeong Lee , Byung-Jun Lee

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input. However, these models fail to convey appropriate spatial composition specified by a layout…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jiayu Xiao , Henglei Lv , Liang Li , Shuhui Wang , Qingming Huang

Video generation models are revolutionizing content creation, with image-to-video models drawing increasing attention due to their enhanced controllability, visual consistency, and practical applications. However, despite their popularity,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Wenhao Wang , Yi Yang

Recent advancements in diffusion models have notably improved the perceptual quality of generated images in text-to-image synthesis tasks. However, diffusion models often struggle to produce images that accurately reflect the intended…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Tiviatis Sim , Kenji Kawaguchi

Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporally coherent video. Compared with broader video generation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Xianlong Wang , Wenbo Pan , Shijia Zhou , Ke Li , Yuqi Wang , Zeyu Ye , Hangtao Zhang , Leo Yu Zhang , Xiaohua Jia

Recently, there have been significant improvements in the quality and performance of text-to-image generation, largely due to the impressive results attained by diffusion models. However, text-to-image diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Wonjun Kang , Kevin Galim , Hyung Il Koo , Nam Ik Cho

Recent advancements in text-to-image diffusion models have demonstrated their remarkable capability to generate high-quality images from textual prompts. However, increasing research indicates that these models memorize and replicate images…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Jie Ren , Yaxin Li , Shenglai Zeng , Han Xu , Lingjuan Lyu , Yue Xing , Jiliang Tang

The problem of text-guided image generation is a complex task in Computer Vision, with various applications, including creating visually appealing artwork and realistic product images. One popular solution widely used for this task is the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Halil Faruk Karagoz , Gulcin Baykal , Irem Arikan Eksi , Gozde Unal

With the increasing use of image generation technology, understanding its social biases, including gender bias, is essential. This paper presents a large-scale study on gender bias in text-to-image (T2I) models, focusing on everyday…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Leander Girrbach , Stephan Alaniz , Genevieve Smith , Zeynep Akata

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

Recent controllable generation approaches such as FreeControl and Diffusion Self-Guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models without training auxiliary modules. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Kuan Heng Lin , Sicheng Mo , Ben Klingher , Fangzhou Mu , Bolei Zhou

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

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

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