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Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image translation, etc. We in this work study the problem of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-11 Gan Sun , Wenqi Liang , Jiahua Dong , Jun Li , Zhengming Ding , Yang Cong

Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing high-fidelity, diverse, and visually realistic images from textual prompts. Despite these advances, existing models struggle with complex prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Eric Hanchen Jiang , Yasi Zhang , Zhi Zhang , Yixin Wan , Andrew Lizarraga , Shufan Li , Ying Nian Wu

Recently, the strong latent Diffusion Probabilistic Model (DPM) has been applied to high-quality Text-to-Image (T2I) generation (e.g., Stable Diffusion), by injecting the encoded target text prompt into the gradually denoised diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Mingyang Yi , Aoxue Li , Yi Xin , Zhenguo Li

Despite recent significant strides achieved by diffusion-based Text-to-Image (T2I) models, current systems are still less capable of ensuring decent compositional generation aligned with text prompts, particularly for the multi-object…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Zhipeng Bao , Yijun Li , Krishna Kumar Singh , Yu-Xiong Wang , Martial Hebert

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

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-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturbing imagery when provided with harmful inputs. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

Recent advances in text-to-image (T2I) generation have led to impressive visual results. However, these models still face significant challenges when handling complex prompt, particularly those involving multiple subjects with distinct…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Lifeng Chen , Jiner Wang , Zihao Pan , Beier Zhu , Xiaofeng Yang , Chi Zhang

Text-to-image (T2I) diffusion models (DMs) have shown promise in generating high-quality images from textual descriptions. The real-world applications of these models require particular attention to their safety and fidelity, but this has…

Cryptography and Security · Computer Science 2023-06-26 Hongcheng Gao , Hao Zhang , Yinpeng Dong , Zhijie Deng

Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincing images following an input text prompt. The goal of image…

Computer Vision and Pattern Recognition · Computer Science 2023-09-28 Kai Wang , Fei Yang , Shiqi Yang , Muhammad Atif Butt , Joost van de Weijer

Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align the generated images with the prompts due to their limited…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Ruichen Wang , Zekang Chen , Chen Chen , Jian Ma , Haonan Lu , Xiaodong Lin

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren

Despite their impressive capabilities, diffusion-based text-to-image (T2I) models can lack faithfulness to the text prompt, where generated images may not contain all the mentioned objects, attributes or relations. To alleviate these…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Shyamgopal Karthik , Karsten Roth , Massimiliano Mancini , Zeynep Akata

Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

While recent text-to-image (T2I) models show impressive capabilities in synthesizing images from brief descriptions, their performance significantly degrades when confronted with long, detail-intensive prompts required in professional…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qirui Jiao , Daoyuan Chen , Yilun Huang , Xika Lin , Ying Shen , Yaliang Li

Text-to-image (T2I) diffusion models, with their impressive generative capabilities, have been adopted for image editing tasks, demonstrating remarkable efficacy. However, due to attention leakage and collision between the cross-attention…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Xingxi Yin , Zhi Li , Jingfeng Zhang , Chenglin Li , Yin Zhang

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

Despite recent advances, diffusion-based text-to-image models still struggle with accurate text rendering. Several studies have proposed fine-tuning or training-free refinement methods for accurate text rendering. However, the critical…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Kanghyun Baek , Sangyub Lee , Jin Young Choi , Jaewoo Song , Daemin Park , Jooyoung Choi , Chaehun Shin , Bohyung Han , Sungroh Yoon

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processing text prompts containing multiple entities and attributes.…

Computation and Language · Computer Science 2024-04-23 Yihang Wu , Xiao Cao , Kaixin Li , Zitan Chen , Haonan Wang , Lei Meng , Zhiyong Huang
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