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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…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Huancheng Chen , Jingtao Li , Weiming Zhuang , Haris Vikalo , Lingjuan Lyu

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…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Diffusion models have demonstrated high-quality performance in conditional text-to-image generation, particularly with structural cues such as edges, layouts, and depth. However, lighting conditions have received limited attention and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Ryugo Morita , Stanislav Frolov , Brian Bernhard Moser , Ko Watanabe , Riku Takahashi , Andreas Dengel

Recent breakthroughs in text-to-image diffusion models have significantly advanced the generation of high-fidelity, photo-realistic images from textual descriptions. Yet, these models often struggle with interpreting spatial arrangements…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Jiaqi Liu , Tao Huang , Chang Xu

Text-to-Image models have introduced a remarkable leap in the evolution of machine learning, demonstrating high-quality synthesis of images from a given text-prompt. However, these powerful pretrained models still lack control handles that…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Andrey Voynov , Kfir Aberman , Daniel Cohen-Or

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

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

Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures. Among these, there are diffusion-based models that have demonstrated…

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…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide vector sketch synthesis. In this paper, we introduce DiffSketcher, a novel algorithm for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Ximing Xing , Chuang Wang , Haitao Zhou , Jing Zhang , Qian Yu , Dong Xu

Although diffusion models exhibit impressive generative capabilities, existing methods for stylized image generation based on these models often require textual inversion or fine-tuning with style images, which is time-consuming and limits…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xin Ma , Yaohui Wang , Xinyuan Chen , Tien-Tsin Wong , Cunjian Chen

Large-scale text-guided image diffusion models have shown astonishing results in text-to-image (T2I) generation. However, applying these models to synthesize textures for 3D geometries remains challenging due to the domain gap between 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Jiawei Lu , Yingpeng Zhang , Zengjun Zhao , He Wang , Kun Zhou , Tianjia Shao

Recent advances in vision-language models have facilitated progress in sketch generation. However, existing specialized methods primarily focus on generic synthesis and lack mechanisms for precise control over sketch styles. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Tengjie Li , Shikui Tu , Lei Xu

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…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion model. Learning a video diffusion model in the latent space…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Jie An , Songyang Zhang , Harry Yang , Sonal Gupta , Jia-Bin Huang , Jiebo Luo , Xi Yin

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

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…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Structural guidance in an image-to-image translation allows intricate control over the shapes of synthesized images. Generating high-quality realistic images from user-specified rough hand-drawn sketches is one such task that aims to impose…

Graphics · Computer Science 2025-02-24 Prasun Roy , Saumik Bhattacharya , Subhankar Ghosh , Umapada Pal , Michael Blumenstein

The rapid advancement of pretrained text-driven diffusion models has significantly enriched applications in image generation and editing. However, as the demand for personalized content editing increases, new challenges emerge especially…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Rui Jiang , Xinghe Fu , Guangcong Zheng , Teng Li , Taiping Yao , Xi Li

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input. However, these models fail to convey appropriate spatial composition specified by a layout…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jiayu Xiao , Henglei Lv , Liang Li , Shuhui Wang , Qingming Huang
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