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Text-to-image (T2I) diffusion models such as SDXL and FLUX have achieved impressive photorealism, yet small-scale distortions remain pervasive in limbs, face, text and so on. Existing refinement approaches either perform costly iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shaocheng Shen , Jianfeng Liang , Chunlei Cai , Cong Geng , Huiyu Duan , Xiaoyun Zhang , Qiang Hu , Guangtao Zhai

In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis. Our framework categorizes evaluations into two distinct groups: first,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Muxi Chen , Yi Liu , Jian Yi , Changran Xu , Qiuxia Lai , Hongliang Wang , Tsung-Yi Ho , Qiang Xu

Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user intent.Our proposed framework, TDRI (Two-Phase Dialogue…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuheng Feng , Jianhui Wang , Kun Li , Sida Li , Tianyu Shi , Haoyue Han , Miao Zhang , Xueqian Wang

Text-to-image (T2I) generation has made significant advances in recent years, but challenges still remain in the generation of perceptual artifacts, misalignment with complex prompts, and safety. The prevailing approach to address these…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Xiaoying Xing , Avinab Saha , Junfeng He , Susan Hao , Paul Vicol , Moonkyung Ryu , Gang Li , Sahil Singla , Sarah Young , Yinxiao Li , Feng Yang , Deepak Ramachandran

Personalized text-to-image (T2I) models not only produce lifelike and varied visuals but also allow users to tailor the images to fit their personal taste. These personalization techniques can grasp the essence of a concept through a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Ye Wang , Zili Yi , Rui Ma

Translating information between text and image is a fundamental problem in artificial intelligence that connects natural language processing and computer vision. In the past few years, performance in image caption generation has seen…

Computer Vision and Pattern Recognition · Computer Science 2017-06-06 Hao Dong , Jingqing Zhang , Douglas McIlwraith , Yike Guo

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

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic images. Despite the progress, these models still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Oscar Mañas , Pietro Astolfi , Melissa Hall , Candace Ross , Jack Urbanek , Adina Williams , Aishwarya Agrawal , Adriana Romero-Soriano , Michal Drozdzal

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

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

Despite recent progress in text-to-image (T2I) generation, existing models often struggle to faithfully capture user intentions from short and under-specified prompts. While prior work has attempted to enhance prompts using large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Mingrui Wu , Lu Wang , Pu Zhao , Fangkai Yang , Jianjin Zhang , Jianfeng Liu , Yuefeng Zhan , Weihao Han , Hao Sun , Jiayi Ji , Xiaoshuai Sun , Qingwei Lin , Weiwei Deng , Dongmei Zhang , Feng Sun , Qi Zhang , Rongrong Ji

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

Modern text-to-image (T2I) models generate high-fidelity visuals but remain indifferent to individual user preferences. While existing reward models optimize for "average" human appeal, they fail to capture the inherent subjectivity of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Anne-Sofie Maerten , Juliane Verwiebe , Shyamgopal Karthik , Ameya Prabhu , Johan Wagemans , Matthias Bethge

The objective of text-to-image (T2I) personalization is to customize a diffusion model to a user-provided reference concept, generating diverse images of the concept aligned with the target prompts. Conventional methods representing the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Jisu Nam , Heesu Kim , DongJae Lee , Siyoon Jin , Seungryong Kim , Seunggyu Chang

In text-to-image models, consistent character generation is the task of achieving text alignment while maintaining the subject's appearance across different prompts. However, since style and appearance are often entangled, the existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yohai Mazuz , Janna Bruner , Lior Wolf

Recent text-to-image (T2I) models generate semantically coherent images from textual prompts, yet evaluating how well they align with individual user preferences remains an open challenge. Conventional evaluation methods, general reward…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Jeongeun Lee , Ryang Heo , Dongha Lee

TIPO (Text-to-Image Prompt Optimization) introduces an efficient approach for automatic prompt refinement in text-to-image (T2I) generation. Starting from simple user prompts, TIPO leverages a lightweight pre-trained model to expand these…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Shih-Ying Yeh , Yi Li , Sang-Hyun Park , Giyeong Oh , Xuehai Wang , Min Song , Youngjae Yu , Shang-Hong Lai

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

Diffusion-driven text-to-image (T2I) generation has achieved remarkable advancements in recent years. To further improve T2I models' capability in numerical and spatial reasoning, layout is employed as an intermedium to bridge large…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yuhao Jia , Wenhan Tan

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka