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Recently, many text-to-image diffusion models have excelled at generating high-resolution images from text but struggle with precise control over spatial composition and object counting. To address these challenges, prior works have…

计算机视觉与模式识别 · 计算机科学 2026-03-24 Huancheng Chen , Jingtao Li , Weiming Zhuang , Haris Vikalo , Lingjuan Lyu

Text-to-image (T2I) generative diffusion models have demonstrated outstanding performance in synthesizing diverse, high-quality visuals from text captions. Several layout-to-image models have been developed to control the generation process…

计算机视觉与模式识别 · 计算机科学 2025-02-11 Ahmad Süleyman , Göksel Biricik

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

计算机视觉与模式识别 · 计算机科学 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

计算机视觉与模式识别 · 计算机科学 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

计算机视觉与模式识别 · 计算机科学 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

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…

计算机视觉与模式识别 · 计算机科学 2026-03-10 Yuhao Jia , Wenhan Tan

Based on recent advanced diffusion models, Text-to-image (T2I) generation models have demonstrated their capabilities to generate diverse and high-quality images. However, leveraging their potential for real-world content creation,…

计算机视觉与模式识别 · 计算机科学 2025-05-08 Sandra Zhang Ding , Jiafeng Mao , Kiyoharu Aizawa

Diffusion models have emerged as a dominant paradigm for generative modeling across a wide range of domains, including prompt-conditional generation. The vast majority of samplers, however, rely on forward discretization of the reverse…

计算机视觉与模式识别 · 计算机科学 2025-12-01 Zhenghan Fang , Jian Zheng , Qiaozi Gao , Xiaofeng Gao , Jeremias Sulam

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…

计算机视觉与模式识别 · 计算机科学 2024-02-01 Zhipeng Bao , Yijun Li , Krishna Kumar Singh , Yu-Xiong Wang , Martial Hebert

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…

计算机视觉与模式识别 · 计算机科学 2026-01-22 Chongbin Yi , Yuxin Liang , Ziqi Zhou , Peng Yang

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

计算机视觉与模式识别 · 计算机科学 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative…

计算机视觉与模式识别 · 计算机科学 2025-01-14 Jiaxin Cheng , Zixu Zhao , Tong He , Tianjun Xiao , Yicong Zhou , Zheng Zhang

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

计算机视觉与模式识别 · 计算机科学 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models struggle to achieve precise text-to-image alignment within cross-attention maps during the…

计算机视觉与模式识别 · 计算机科学 2026-05-28 Shipeng Cao , Biao Qian , Haipeng Liu , Yang Wang , Meng Wang

Text-to-image (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation scenarios such as prompt iteration, agent-based generation, and flow-grpo. We reveal a…

计算机视觉与模式识别 · 计算机科学 2026-03-27 Benlei Cui , Bukun Huang , Zhizeng Ye , Xuemei Dong , Tuo Chen , Hui Xue , Dingkang Yang , Longtao Huang , Jingqun Tang , Haiwen Hong

Existing text-to-image diffusion models struggle to synthesize realistic images given dense captions, where each text prompt provides a detailed description for a specific image region. To address this, we propose DenseDiffusion, a…

计算机视觉与模式识别 · 计算机科学 2023-08-25 Yunji Kim , Jiyoung Lee , Jin-Hwa Kim , Jung-Woo Ha , Jun-Yan Zhu

Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage of diffusion models to generate the high-quality object…

计算机视觉与模式识别 · 计算机科学 2024-02-20 Kai Chen , Enze Xie , Zhe Chen , Yibo Wang , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung

Controllable image generation has always been one of the core demands in image generation, aiming to create images that are both creative and logical while satisfying additional specified conditions. In the post-AIGC era, controllable…

计算机视觉与模式识别 · 计算机科学 2024-11-12 Guandong Li

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…

计算机视觉与模式识别 · 计算机科学 2025-05-14 Tianyi Liang , Jiangqi Liu , Yifei Huang , Shiqi Jiang , Jianshen Shi , Changbo Wang , Chenhui Li

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…

计算机视觉与模式识别 · 计算机科学 2023-11-30 Xiaohui Chen , Yongfei Liu , Yingxiang Yang , Jianbo Yuan , Quanzeng You , Li-Ping Liu , Hongxia Yang
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