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Graph generation is a critical yet challenging task, as empirical analyses require a deep understanding of complex, non-Euclidean structures. Diffusion models have recently made significant advances in graph generation, but these models are…

Machine Learning · Computer Science 2026-03-13 Yiming Huang , Tolga Birdal

Diffusion models have demonstrated their ability to generate diverse and high-quality images, sparking considerable interest in their potential for real image editing applications. However, existing diffusion-based approaches for local…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Wenjing Huang , Shikui Tu , Lei Xu

Diffusion models have emerged as a promising approach for text generation, with recent works falling into two main categories: discrete and continuous diffusion models. Discrete diffusion models apply token corruption independently using…

Computation and Language · Computer Science 2025-05-29 Bocheng Li , Zhujin Gao , Linli Xu

The art of communication beyond speech there are gestures. The automatic co-speech gesture generation draws much attention in computer animation. It is a challenging task due to the diversity of gestures and the difficulty of matching the…

Human-Computer Interaction · Computer Science 2023-05-09 Sicheng Yang , Zhiyong Wu , Minglei Li , Zhensong Zhang , Lei Hao , Weihong Bao , Ming Cheng , Long Xiao

The problem of text-guided image generation is a complex task in Computer Vision, with various applications, including creating visually appealing artwork and realistic product images. One popular solution widely used for this task is the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Halil Faruk Karagoz , Gulcin Baykal , Irem Arikan Eksi , Gozde Unal

In industrial equipment monitoring, fault diagnosis is critical for ensuring system reliability and enabling predictive maintenance. However, the scarcity of fault data, due to the rarity of fault events and the high cost of data…

Machine Learning · Computer Science 2025-11-20 Yi Xu , Zhigang Chen , Rui Wang , Yangfan Li , Fengxiao Tang , Ming Zhao , Jiaqi Liu

Recent advances in diffusion models have driven remarkable progress in image generation. However, the generation process remains computationally intensive, and users often need to iteratively refine prompts to achieve the desired results,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Yi Wei , Shunpu Tang , Liang Zhao , Qiangian Yang

The generation of stylistic 3D facial animations driven by speech presents a significant challenge as it requires learning a many-to-many mapping between speech, style, and the corresponding natural facial motion. However, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Zhiyao Sun , Tian Lv , Sheng Ye , Matthieu Lin , Jenny Sheng , Yu-Hui Wen , Minjing Yu , Yong-Jin Liu

Beyond high-fidelity image synthesis, diffusion models have recently exhibited promising results in dense visual perception tasks. However, most existing work treats diffusion models as a standalone component for perception tasks, employing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Shuhong Zheng , Zhipeng Bao , Ruoyu Zhao , Martial Hebert , Yu-Xiong Wang

Scene text editing aims to modify or add texts on images while ensuring text fidelity and overall visual quality consistent with the background. Recent methods are primarily built on UNet-based diffusion models, which have improved scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Rui Lan , Yancheng Bai , Xu Duan , Mingxing Li , Dongyang Jin , Ryan Xu , Dong Nie , Lei Sun , Xiangxiang Chu

Generative modeling has recently undergone remarkable advancements, primarily propelled by the transformative implications of Diffusion Probabilistic Models (DPMs). The impressive capability of these models, however, often entails…

Machine Learning · Computer Science 2023-10-03 Gongfan Fang , Xinyin Ma , Xinchao Wang

Diffusion Models (DMs) have achieved great success in image generation and other fields. By fine sampling through the trajectory defined by the SDE/ODE solver based on a well-trained score model, DMs can generate remarkable high-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Bowen Zheng , Tianming Yang

A few-shot font generation (FFG) method has to satisfy two objectives: the generated images should preserve the underlying global structure of the target character and present the diverse local reference style. Existing FFG methods aim to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Song Park , Sanghyuk Chun , Junbum Cha , Bado Lee , Hyunjung Shim

Layout generation is a foundation task of graphic design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yu Li , Yifan Chen , Gongye Liu , Fei Yin , Qingyan Bai , Jie Wu , Hongfa Wang , Ruihang Chu , Yujiu Yang

Chinese vector font generation is challenging due to the complex structure and huge amount of Chinese characters. Recent advances remain limited to generating a small set of characters with simple structure. In this work, we first observe…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Jinyu Song , Weitao You , Shuhui Shi , Shuxuan Guo , Lingyun Sun , Wei Wang

Diffusion models are well known for their ability to generate a high-fidelity image for an input prompt through an iterative denoising process. Unfortunately, the high fidelity also comes at a high computational cost due the inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Qinchan Li , Kenneth Chen , Changyue Su , Wittawat Jitkrittum , Qi Sun , Patsorn Sangkloy

Generative models now produce images with such stunning realism that they can easily deceive the human eye. While this progress unlocks vast creative potential, it also presents significant risks, such as the spread of misinformation.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Yichi Zhang , Xiaogang Xu

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

We provide an overview of the diffusion model as a method to generate new samples. Generative models have been recently adopted for tasks such as art generation (Stable Diffusion, Dall-E) and text generation (ChatGPT). Diffusion models in…

Machine Learning · Statistics 2025-06-13 Justin Le

Diffusion-based generative modeling has been achieving state-of-the-art results on various generation tasks. Most diffusion models, however, are limited to a single-generation modeling. Can we generalize diffusion models with the ability of…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Changyou Chen , Han Ding , Bunyamin Sisman , Yi Xu , Ouye Xie , Benjamin Z. Yao , Son Dinh Tran , Belinda Zeng
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