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Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T2I) synthesis. However, many existing systems rely on explicit modality switching,…

The goal of a speech-to-image transform is to produce a photo-realistic picture directly from a speech signal. Recently, various studies have focused on this task and have achieved promising performance. However, current speech-to-image…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Zhenxing Zhang , Lambert Schomaker

This work addresses the challenge of quantifying originality in text-to-image (T2I) generative diffusion models, with a focus on copyright originality. We begin by evaluating T2I models' ability to innovate and generalize through controlled…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Adi Haviv , Shahar Sarfaty , Uri Hacohen , Niva Elkin-Koren , Roi Livni , Amit H Bermano

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

Stable Diffusion has advanced text-to-image synthesis, but training models to generate images with accurate object quantity is still difficult due to the high computational cost and the challenge of teaching models the abstract concept of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Yanyu Li , Pencheng Wan , Liang Han , Yaowei Wang , Liqiang Nie , Min Zhang

Text-to-image (T2I) generation has greatly enhanced creative expression, yet achieving preference-aligned generation in a real-time and training-free manner remains challenging. Previous methods often rely on static, pre-collected…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Yang Li , Songlin Yang , Xiaoxuan Han , Wei Wang , Jing Dong , Yueming Lyu , Ziyu Xue

Text-to-image (T2I) diffusion models have achieved remarkable success in generating high-quality images from textual prompts. However, their ability to store vast amounts of knowledge raises concerns in scenarios where selective forgetting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Gen Li , Yang Xiao , Jie Ji , Kaiyuan Deng , Bo Hui , Linke Guo , Xiaolong Ma

Controllable text-to-image generation synthesizes visual text and objects in images with certain conditions, which are frequently applied to emoji and poster generation. Visual text rendering and layout-to-image generation tasks have been…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xiaoran Zhao , Tianhao Wu , Yu Lai , Zhiliang Tian , Zhen Huang , Yahui Liu , Zejiang He , Dongsheng Li

Diffusion models have revitalized the image generation domain, playing crucial roles in both academic research and artistic expression. With the emergence of new diffusion models, assessing the performance of text-to-image models has become…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Chutian Meng , Fan Ma , Jiaxu Miao , Chi Zhang , Yi Yang , Yueting Zhuang

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

Artificial Intelligence-Generated Content (AIGC) has made significant strides, with high-resolution text-to-image (T2I) generation becoming increasingly critical for improving users' Quality of Experience (QoE). Although…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Chongbin Yi , Yuxin Liang , Ziqi Zhou , Peng Yang

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

In text-to-video (T2V) generation, significant attention has been directed toward its development, yet unifying discrete and continuous grounding conditions in T2V generation remains under-explored. This paper proposes a Grounded…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Huanzhang Dou , Ruixiang Li , Wei Su , Xi Li

Text-to-Image generation has evolved from basic image synthesis into a frequently used core capability in professional creative workflows, where simple text-image alignment can no longer satisfy users' pressing demands for faithful…

Text-to-image (T2I) generation has made remarkable progress, yet existing systems still lack intuitive control over spatial composition, object consistency, and multi-step editing. We present $\textbf{LayerCraft}$, a modular framework that…

Machine Learning · Computer Science 2025-10-20 Yuyao Zhang , Jinghao Li , Yu-Wing Tai

We present a novel image editing scenario termed Text-grounded Object Generation (TOG), defined as generating a new object in the real image spatially conditioned by textual descriptions. Existing diffusion models exhibit limitations of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Xiangtian Xue , Jiasong Wu , Youyong Kong , Lotfi Senhadji , Huazhong Shu

Text to image generation methods (T2I) are widely popular in generating art and other creative artifacts. While visual hallucinations can be a positive factor in scenarios where creativity is appreciated, such artifacts are poorly suited…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Rodrigo Valerio , Joao Bordalo , Michal Yarom , Yonatan Bitton , Idan Szpektor , Joao Magalhaes

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

Despite the impressive advances in text-to-image models, they often struggle to effectively compose complex scenes with multiple objects, displaying various attributes and relationships. To address this challenge, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Kaiyi Huang , Chengqi Duan , Kaiyue Sun , Enze Xie , Zhenguo Li , Xihui Liu