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A significant ``modality gap" exists between the abundance of text-only data and the increasing power of multimodal models. This work systematically investigates whether images generated on-the-fly by Text-to-Image (T2I) models can serve as…

Multimedia · Computer Science 2026-03-04 Yuesheng Huang , Peng Zhang , Xiaoxin Wu , Riliang Liu , Jiaqi Liang

Text-to-image diffusion models have recently received increasing interest for their astonishing ability to produce high-fidelity images from solely text inputs. Subsequent research efforts aim to exploit and apply their capabilities to real…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Manuel Brack , Felix Friedrich , Katharina Kornmeier , Linoy Tsaban , Patrick Schramowski , Kristian Kersting , Apolinário Passos

One challenge in text-to-image (T2I) generation is the inadvertent reflection of culture gaps present in the training data, which signifies the disparity in generated image quality when the cultural elements of the input text are rarely…

Computer Vision and Pattern Recognition · Computer Science 2023-07-07 Bingshuai Liu , Longyue Wang , Chenyang Lyu , Yong Zhang , Jinsong Su , Shuming Shi , Zhaopeng Tu

Image-to-image (I2I) translation is usually carried out among discrete domains. However, image domains, often corresponding to a physical value, are usually continuous. In other words, images gradually change with the value, and there…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Qiusheng Huang , Xueqi Hu , Li Sun , Qingli Li

While recent advancements in artificial intelligence (AI) language models demonstrate cutting-edge performance when working with English texts, equivalent models do not exist in other languages or do not reach the same performance level.…

Computation and Language · Computer Science 2022-12-26 Noga Mudrik , Adam S. Charles

Thanks to the powerful language comprehension capabilities of Large Language Models (LLMs), existing instruction-based image editing methods have introduced Multimodal Large Language Models (MLLMs) to promote information exchange between…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yujie Hu , Zecheng Tang , Xu Jiang , Weiqi Li , Jian Zhang

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

In Text-to-Image (T2I) generation, the complexity of entities and their intricate interactions pose a significant challenge for T2I method based on diffusion model: how to effectively control entity and their interactions to produce…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Mingyue Yang , Dianxi Shi , Jialu Zhou , Xinyu Wei , Leqian Li , Shaowu Yang , Chunping Qiu

Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on specific text prompts. However, existing T2I-based methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Salaheldin Mohamed , Dong Han , Yong Li

Text-to-image (T2I) models based on diffusion processes have achieved remarkable success in controllable image generation using user-provided captions. However, the tight coupling between the current text encoder and image decoder in T2I…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Ning Yu , Chen Xing , Shu Zhang , Zeyuan Chen , Stefano Ermon , Yun Fu , Caiming Xiong , Ran Xu

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability…

Human-Computer Interaction · Computer Science 2025-06-13 Bao Zhang , Zihan Li , Zhenglei Liu , Huanchen Wang , Yuxin Ma

Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment. However, these models can also be misused to produce inappropriate content. Existing safety measures,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hongxiang Zhang , Yifeng He , Hao Chen

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Yijun Yang , Ruiyuan Gao , Xiao Yang , Jianyuan Zhong , Qiang Xu

Existing text-to-image (T2I) benchmarks largely rely on fixed prompt sets, leaving them vulnerable to overfitting and benchmark contamination once publicly released and repeatedly reused. In this work, we propose DynT2I-Eval, a fully…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Juntong Wang , Jiarui Wang , Huiyu Duan , Lewei Li , Guangtao Zhai , Xiongkuo Min

Text-to-image (T2I) models have made substantial progress in generating images from textual prompts. However, they frequently fail to produce images consistent with physical commonsense, a vital capability for applications in world…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Fanqing Meng , Wenqi Shao , Lixin Luo , Yahong Wang , Yiran Chen , Quanfeng Lu , Yue Yang , Tianshuo Yang , Kaipeng Zhang , Yu Qiao , Ping Luo

Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Narek Tumanyan , Michal Geyer , Shai Bagon , Tali Dekel

We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoregressive model, our method addresses two key challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Jihun Park , Kyoungmin Lee , Jongmin Gim , Hyeonseo Jo , Minseok Oh , Wonhyeok Choi , Kyumin Hwang , Jaeyeul Kim , Minwoo Choi , Sunghoon Im

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
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