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We provide an attention-level control method for the task of coupled image generation, where "coupled" means that multiple simultaneously generated images are expected to have the same or very similar backgrounds. While backgrounds coupled,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Chenfei Yuan , Nanshan Jia , Hangqi Li , Peter W. Glynn , Zeyu Zheng

Despite the existence of numerous colorization methods, several limitations still exist, such as lack of user interaction, inflexibility in local colorization, unnatural color rendering, insufficient color variation, and color overflow. To…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Zhexin Liang , Zhaochen Li , Shangchen Zhou , Chongyi Li , Chen Change Loy

The consistent mapping from poems to paintings is essential for the research and restoration of traditional Chinese gardens. But the lack of firsthand ma-terial is a great challenge to the reconstruction work. In this paper, we pro-pose a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Jiaxi Shi1 , Hao Hua1

With the recent drastic advancements in text-to-video diffusion models, controlling their generations has drawn interest. A popular way for control is through bounding boxes or layouts. However, enforcing adherence to these control inputs…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Daniel Ajisafe , Eric Hedlin , Helge Rhodin , Kwang Moo Yi

Advancements in generative models have enabled image inpainting models to generate content within specific regions of an image based on provided prompts and masks. However, existing inpainting methods often suffer from problems such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Jun Huang , Ting Liu , Yihang Wu , Xiaochao Qu , Luoqi Liu , Xiaolin Hu

While generative models produce high-quality images of concepts learned from a large-scale database, a user often wishes to synthesize instantiations of their own concepts (for example, their family, pets, or items). Can we teach a model to…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Nupur Kumari , Bingliang Zhang , Richard Zhang , Eli Shechtman , Jun-Yan Zhu

Existing approaches for controlling text-to-image diffusion models, while powerful, do not allow for explicit 3D object-centric control, such as precise control of object orientation. In this work, we address the problem of multi-object…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Rishubh Parihar , Vaibhav Agrawal , Sachidanand VS , R. Venkatesh Babu

This study proposes a UI interface generation method based on a diffusion model, aiming to achieve high-quality, diversified, and personalized interface design through generative artificial intelligence technology. The diffusion model is…

Human-Computer Interaction · Computer Science 2025-03-27 Yifei Duan , Liuqingqing Yang , Tong Zhang , Zhijun Song , Fenghua Shao

Recent diffusion-based generative models show promise in their ability to generate text images, but limitations in specifying the styles of the generated texts render them insufficient in the realm of typographic design. This paper proposes…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 KhayTze Peong , Seiichi Uchida , Daichi Haraguchi

The controllability of 3D object generation methods is achieved through input text. Existing text-to-3D object generation methods primarily focus on generating a single object based on a single object description. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Shaorong Sun , Shuchao Pang , Yazhou Yao , Xiaoshui Huang

Multi-view consistency remains a challenge for image diffusion models. Even within the Text-to-Texture problem, where perfect geometric correspondences are known a priori, many methods fail to yield aligned predictions across views,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Shimon Vainer , Konstantin Kutsy , Dante De Nigris , Ciara Rowles , Slava Elizarov , Simon Donné

Digital art synthesis is receiving increasing attention in the multimedia community because of engaging the public with art effectively. Current digital art synthesis methods usually use single-modality inputs as guidance, thereby limiting…

Computer Vision and Pattern Recognition · Computer Science 2022-09-29 Nisha Huang , Fan Tang , Weiming Dong , Changsheng Xu

Color is an essential component of graphic design, acting not only as a visual factor but also carrying cultural implications. However, existing research on algorithmic color palette generation and colorization largely ignores the cultural…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yufan Li , Jinggang Zhuo , Ling Fan , Harry Jiannan Wang

Although significant advancements have been achieved in the progress of keypoint-guided Text-to-Image diffusion models, existing mainstream keypoint-guided models encounter challenges in controlling the generation of more general non-rigid…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Qin Guo , Ailing Zeng , Dongxu Yue , Ceyuan Yang , Yang Cao , Hanzhong Guo , Fei Shen , Wei Liu , Xihui Liu , Dan Xu

ControlNet offers a powerful way to guide diffusion-based generative models, yet most implementations rely on ad-hoc heuristics to choose which network blocks to control-an approach that varies unpredictably with different tasks. To address…

Machine Learning · Computer Science 2025-02-21 Zheng Fang , Lichuan Xiang , Xu Cai , Kaicheng Zhou , Hongkai Wen

In this work, we propose MetaScript, a novel Chinese content generation system designed to address the diminishing presence of personal handwriting styles in the digital representation of Chinese characters. Our approach harnesses the power…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Xiangyuan Xue , Kailing Wang , Jiazi Bu , Qirui Li , Zhiyuan Zhang

Recently, there is a growing interest in creating computer-aided design (CAD) models based on user intent, known as controllable CAD generation. Existing work offers limited controllability and needs separate models for different types of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Zhanwei Zhang , Shizhao Sun , Wenxiao Wang , Deng Cai , Jiang Bian

Ambigrams are graphical letter designs that can be read not only from the original direction but also from a rotated direction (especially with 180 degrees). Designing ambigrams is difficult even for human experts because keeping their dual…

Computer Vision and Pattern Recognition · Computer Science 2023-06-22 Takahiro Shirakawa , Seiichi Uchida

The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Shitao Xiao , Yueze Wang , Junjie Zhou , Huaying Yuan , Xingrun Xing , Ruiran Yan , Chaofan Li , Shuting Wang , Tiejun Huang , Zheng Liu

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang
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