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Recently, the application of modern diffusion-based text-to-image generation models for creating artistic fonts, traditionally the domain of professional designers, has garnered significant interest. Diverging from the majority of existing…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Xinzhi Mu , Li Chen , Bohan Chen , Shuyang Gu , Jianmin Bao , Dong Chen , Ji Li , Yuhui Yuan

Animating hand-drawn sketches using traditional tools is challenging and complex. Sketches provide a visual basis for explanations, and animating these sketches offers an experience of real-time scenarios. We propose an approach for…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Gaurav Rai , Ojaswa Sharma

For an artist or a graphic designer, the spatial layout of a scene is a critical design choice. However, existing text-to-image diffusion models provide limited support for incorporating spatial information. This paper introduces Composite…

Computer Vision and Pattern Recognition · Computer Science 2023-07-27 Vikram Jamwal , Ramaneswaran S

We present a new method for text-driven motion transfer - synthesizing a video that complies with an input text prompt describing the target objects and scene while maintaining an input video's motion and scene layout. Prior methods are…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Danah Yatim , Rafail Fridman , Omer Bar-Tal , Yoni Kasten , Tali Dekel

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Tasin Islam , Alina Miron , XiaoHui Liu , Yongmin Li

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…

Computer Vision and Pattern Recognition · Computer Science 2023-08-25 Yunji Kim , Jiyoung Lee , Jin-Hwa Kim , Jung-Woo Ha , Jun-Yan Zhu

In this paper, we propose a diffusion probabilistic model for handwriting generation. Diffusion models are a class of generative models where samples start from Gaussian noise and are gradually denoised to produce output. Our method of…

Machine Learning · Computer Science 2020-11-16 Troy Luhman , Eric Luhman

Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style image and a 3D mesh with its text description. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Zhiyu Xie , Yuqing Zhang , Xiangjun Tang , Yiqian Wu , Dehan Chen , Gongsheng Li , Xaogang Jin

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

While diffusion models have revolutionized text-to-image generation with their ability to synthesize realistic and diverse scenes, they continue to struggle to generate consistent and legible text within images. This shortcoming is commonly…

Machine Learning · Computer Science 2025-09-16 Tianyu Zhang , Xinyu Wang , Lu Li , Zhenghan Tai , Jijun Chi , Jingrui Tian , Hailin He , Suyuchen Wang

Given a 3D mesh with a UV parameterization, we introduce a novel approach to generating textures from text prompts. While prior work uses optimization from Text-to-Image Diffusion models to generate textures and geometry, this is slow and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Julian Knodt , Xifeng Gao

Text-driven human motion generation in computer vision is both significant and challenging. However, current methods are limited to producing either deterministic or imprecise motion sequences, failing to effectively control the temporal…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Yin Wang , Zhiying Leng , Frederick W. B. Li , Shun-Cheng Wu , Xiaohui Liang

Text-driven motion generation offers a powerful and intuitive way to create human movements directly from natural language. By removing the need for predefined motion inputs, it provides a flexible and accessible approach to controlling…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Ali Rida Sahili , Najett Neji , Hedi Tabia

Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obtaining accurate human annotations is labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Ling Fu , Zijie Wu , Yingying Zhu , Yuliang Liu , Xiang Bai

Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models for motion generation has enabled improvements in the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Samaneh Azadi , Akbar Shah , Thomas Hayes , Devi Parikh , Sonal Gupta

Latent diffusion models such as Stable Diffusion achieve state-of-the-art results on text-to-image generation tasks. However, the extent to which these models have a semantic understanding of the images they generate is not well understood.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Cameron Braunstein , Mariya Toneva , Eddy Ilg

Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fine-tuned on massive 3D data, offering the capability of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Zeyu Yang , Zijie Pan , Chun Gu , Li Zhang

Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Nicolas Cherel , Andrés Almansa , Yann Gousseau , Alasdair Newson

Text-to-motion models that generate sequences of human poses from textual descriptions are garnering significant attention. However, due to data scarcity, the range of motions these models can produce is still limited. For instance, current…

Machine Learning · Computer Science 2024-10-14 Clayton Leite , Yu Xiao