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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

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

Text-to-image (T2I) diffusion models generate high-quality images but often fail to capture the spatial relations specified in text prompts. This limitation can be traced to two factors: lack of fine-grained spatial supervision in training…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Sarah Rastegar , Violeta Chatalbasheva , Sieger Falkena , Anuj Singh , Yanbo Wang , Tejas Gokhale , Hamid Palangi , Hadi Jamali-Rad

Recent advancements in image generation have made significant progress, yet existing models present limitations in perceiving and generating an arbitrary number of interrelated images within a broad context. This limitation becomes…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Ying Shen , Yizhe Zhang , Shuangfei Zhai , Lifu Huang , Joshua M. Susskind , Jiatao Gu

Text-to-image generation (TTI) refers to the usage of models that could process text input and generate high fidelity images based on text descriptions. Text-to-image generation using neural networks could be traced back to the emergence of…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Fengxiang Bie , Yibo Yang , Zhongzhu Zhou , Adam Ghanem , Minjia Zhang , Zhewei Yao , Xiaoxia Wu , Connor Holmes , Pareesa Golnari , David A. Clifton , Yuxiong He , Dacheng Tao , Shuaiwen Leon Song

Recent advances in text-to-image (T2I) generation have achieved remarkable visual outcomes through large-scale rectified flow models. However, how these models behave under long prompts remains underexplored. Long prompts encode rich…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Bo-Kai Ruan , Teng-Fang Hsiao , Ling Lo , Yi-Lun Wu , Hong-Han Shuai

Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the color composition while the text prompt provides control…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Jaskirat Singh , Stephen Gould , Liang Zheng

Text-to-image generative models often reflect the biases of the training data, leading to unequal representations of underrepresented groups. This study investigates inclusive text-to-image generative models that generate images based on…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Cheng Zhang , Xuanbai Chen , Siqi Chai , Chen Henry Wu , Dmitry Lagun , Thabo Beeler , Fernando De la Torre

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

Text-driven Image to Video Generation (TI2V) aims to generate controllable video given the first frame and corresponding textual description. The primary challenges of this task lie in two parts: (i) how to identify the target objects and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xingrui Wang , Xin Li , Yaosi Hu , Hanxin Zhu , Chen Hou , Cuiling Lan , Zhibo Chen

Recent advancements in text-to-image models, particularly diffusion models, have shown significant promise. However, compositional text-to-image models frequently encounter difficulties in generating high-quality images that accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Song Wen , Guian Fang , Renrui Zhang , Peng Gao , Hao Dong , Dimitris Metaxas

Diffusion models have exhibit exceptional performance in text-to-image generation and editing. However, existing methods often face challenges when handling complex text prompts that involve multiple objects with multiple attributes and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Zhaochen Yu , Chenlin Meng , Minkai Xu , Stefano Ermon , Bin Cui

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

Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with complex instructions involving multiple objects, attributes, and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yucheng Zhou , Jiahao Yuan , Qianning Wang

Despite the impressive synthesis quality of text-to-image (T2I) diffusion models, their black-box deployment poses significant regulatory challenges: Malicious actors can fine-tune these models to generate illegal content, circumventing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Zhuomeng Zhang , Fangqi Li , Chong Di , Hongyu Zhu , Hanyi Wang , Shilin Wang

We introduce a framework for joint grounded scene graph - image generation, a challenging task involving high-dimensional, multi-modal structured data. To effectively model this complex joint distribution, we adopt a factorized approach:…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Bicheng Xu , Qi Yan , Renjie Liao , Lele Wang , Leonid Sigal

Text-to-image (T2I) generation has made remarkable progress in producing high-quality images, but a fundamental challenge remains: creating backgrounds that naturally accommodate text placement without compromising image quality. This…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Tianyi Liang , Jiangqi Liu , Yifei Huang , Shiqi Jiang , Jianshen Shi , Changbo Wang , Chenhui Li

Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, the application of text-to-image generative models in computer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yulu Gan , Sungwoo Park , Alexander Schubert , Anthony Philippakis , Ahmed M. Alaa

The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Shitao Xiao , Yueze Wang , Junjie Zhou , Huaying Yuan , Xingrun Xing , Ruiran Yan , Chaofan Li , Shuting Wang , Tiejun Huang , Zheng Liu

Optical illusion hidden picture is an interesting visual perceptual phenomenon where an image is cleverly integrated into another picture in a way that is not immediately obvious to the viewer. Established on the off-the-shelf text-to-image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Xiang Gao , Shuai Yang , Jiaying Liu