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Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

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

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

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

With the rapid advancement of intelligent transportation systems, text-driven image generation and editing techniques have demonstrated significant potential in providing rich, controllable visual scene data for applications such as traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Feng Lv , Haoxuan Feng , Zilu Zhang , Chunlong Xia , Yanfeng Li

Large text-to-image diffusion models have impressive capabilities in generating photorealistic images from text prompts. How to effectively guide or control these powerful models to perform different downstream tasks becomes an important…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Zeju Qiu , Weiyang Liu , Haiwen Feng , Yuxuan Xue , Yao Feng , Zhen Liu , Dan Zhang , Adrian Weller , Bernhard Schölkopf

When humans read a specific text, they often visualize the corresponding images, and we hope that computers can do the same. Text-to-image synthesis (T2I), which focuses on generating high-quality images from textual descriptions, has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Nonghai Zhang , Hao Tang

Diffusion model based Text-to-Image has achieved impressive achievements recently. Although current technology for synthesizing images is highly advanced and capable of generating images with high fidelity, it is still possible to give the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Yuxiang Tuo , Wangmeng Xiang , Jun-Yan He , Yifeng Geng , Xuansong Xie

Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further extended these methods with personalization techniques that…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Tanzila Rahman , Shweta Mahajan , Hsin-Ying Lee , Jian Ren , Sergey Tulyakov , Leonid Sigal

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Songwei Ge , Taesung Park , Jun-Yan Zhu , Jia-Bin Huang

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

Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Jingbo Zhang , Xiaoyu Li , Ziyu Wan , Can Wang , Jing Liao

Text-guided image-to-image diffusion models excel in translating images based on textual prompts, allowing for precise and creative visual modifications. However, such a powerful technique can be misused for spreading misinformation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Wenhao Wang , Yifan Sun , Zongxin Yang , Zhentao Tan , Zhengdong Hu , Yi Yang

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlooked is the specific camera geometry used during image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Andrey Voynov , Amir Hertz , Moab Arar , Shlomi Fruchter , Daniel Cohen-Or

Recently, text-to-image (T2I) editing has been greatly pushed forward by applying diffusion models. Despite the visual promise of the generated images, inconsistencies with the expected textual prompt remain prevalent. This paper aims to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Aoxue Li , Mingyang Yi , Zhenguo Li

Text-to-image (T2I) models, such as Stable Diffusion, have exhibited remarkable performance in generating high-quality images from text descriptions in recent years. However, text-to-image models may be tricked into generating…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Xinfeng Li , Yuchen Yang , Jiangyi Deng , Chen Yan , Yanjiao Chen , Xiaoyu Ji , Wenyuan Xu

Despite astonishing progress, generating realistic images of complex scenes remains a challenging problem. Recently, layout-to-image synthesis approaches have attracted much interest by conditioning the generator on a list of bounding boxes…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Stanislav Frolov , Prateek Bansal , Jörn Hees , Andreas Dengel

Generating images with embedded text is crucial for the automatic production of visual and multimodal documents, such as educational materials and advertisements. However, existing diffusion-based text-to-image models often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Forouzan Fallah , Maitreya Patel , Agneet Chatterjee , Vlad I. Morariu , Chitta Baral , Yezhou Yang