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Related papers: A Fast Text-Driven Approach for Generating Artisti…

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Based on recent advanced diffusion models, Text-to-image (T2I) generation models have demonstrated their capabilities to generate diverse and high-quality images. However, leveraging their potential for real-world content creation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Sandra Zhang Ding , Jiafeng Mao , Kiyoharu Aizawa

The artistic style within a painting is the means of expression, which includes not only the painting material, colors, and brushstrokes, but also the high-level attributes including semantic elements, object shapes, etc. Previous arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yuxin Zhang , Nisha Huang , Fan Tang , Haibin Huang , Chongyang Ma , Weiming Dong , Changsheng Xu

Recently, with the rapid advancements of generative models, the field of visual text generation has witnessed significant progress. However, it is still challenging to render high-quality text images in real-world scenarios, as three…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Yuanzhi Zhu , Jiawei Liu , Feiyu Gao , Wenyu Liu , Xinggang Wang , Peng Wang , Fei Huang , Cong Yao , Zhibo Yang

Conditional text-to-image generation is an active area of research, with many possible applications. Existing research has primarily focused on generating a single image from available conditioning information in one step. One practical…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Alaaeldin El-Nouby , Shikhar Sharma , Hannes Schulz , Devon Hjelm , Layla El Asri , Samira Ebrahimi Kahou , Yoshua Bengio , Graham W. Taylor

Since the generative neural networks have made a breakthrough in the image generation problem, lots of researches on their applications have been studied such as image restoration, style transfer and image completion. However, there has…

Computer Vision and Pattern Recognition · Computer Science 2021-10-08 Jeesoo Kim , Jangho Kim , Jaeyoung Yoo , Daesik Kim , Nojun Kwak

Text-to-image diffusion models have demonstrated an impressive ability to produce high-quality outputs. However, they often struggle to accurately follow fine-grained spatial information in an input text. To this end, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Ran Galun , Sagie Benaim

Advances in generative models have led to significant interest in image synthesis, demonstrating the ability to generate high-quality images for a diverse range of text prompts. Despite this progress, most studies ignore the presence of…

Artificial Intelligence · Computer Science 2024-07-02 Nila Masrourisaadat , Nazanin Sedaghatkish , Fatemeh Sarshartehrani , Edward A. Fox

We propose a generative model that, given a coarsely edited image, synthesizes a photorealistic output that follows the prescribed layout. Our method transfers fine details from the original image and preserve the identity of its parts.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Hadi Alzayer , Zhihao Xia , Xuaner Zhang , Eli Shechtman , Jia-Bin Huang , Michael Gharbi

Content creators often draw inspiration from multiple visual sources, combining distinct elements to craft new compositions. Modern computational approaches now aim to emulate this fundamental creative process. Although recent diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Sara Dorfman , Dana Cohen-Bar , Rinon Gal , Daniel Cohen-Or

Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substantial progress, such token sequences inevitably reuse…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jeonghwan Kim , Yushi Lan , Armando Fortes , Yongwei Chen , Xingang Pan

Can a generative model be trained to produce images from a specific domain, guided by a text prompt only, without seeing any image? In other words: can an image generator be trained "blindly"? Leveraging the semantic power of large scale…

Computer Vision and Pattern Recognition · Computer Science 2021-12-17 Rinon Gal , Or Patashnik , Haggai Maron , Gal Chechik , Daniel Cohen-Or

The painting process of artists is inherently stepwise and varies significantly among different painters and styles. Generating detailed, step-by-step painting processes is essential for art education and research, yet remains largely…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yiren Song , Shijie Huang , Chen Yao , Xiaojun Ye , Hai Ci , Jiaming Liu , Yuxuan Zhang , Mike Zheng Shou

Text-to-image generation has made remarkable progress with the emergence of diffusion models. However, it is still a difficult task to generate images for street views based on text, mainly because the road topology of street scenes is…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jinming Su , Songen Gu , Yiting Duan , Xingyue Chen , Junfeng Luo

A creative image-and-text generative AI system mimics humans' extraordinary abilities to provide users with diverse and comprehensive caption suggestions, as well as rich image creations. In this work, we demonstrate such an AI creation…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Yupan Huang , Bei Liu , Jianlong Fu , Yutong Lu

Design prototyping involves creating mockups of products or concepts to gather feedback and iterate on ideas. While prototyping often requires specific parts of objects, such as when constructing a novel creature for a video game, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Mo Zhou , Josh Myers-Dean , Danna Gurari

This paper proposes an image-to-painting translation method that generates vivid and realistic painting artworks with controllable styles. Different from previous image-to-image translation methods that formulate the translation as…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Zhengxia Zou , Tianyang Shi , Shuang Qiu , Yi Yuan , Zhenwei Shi

Controllable painting generation plays a pivotal role in image stylization. Currently, the control way of style transfer is subject to exemplar-based reference or a random one-hot vector guidance. Few works focus on decoupling the intrinsic…

Computer Vision and Pattern Recognition · Computer Science 2020-02-27 Minxuan Lin , Yingying Deng , Fan Tang , Weiming Dong , Changsheng Xu

The text-driven image and video diffusion models have achieved unprecedented success in generating realistic and diverse content. Recently, the editing and variation of existing images and videos in diffusion-based generative models have…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yuyang Zhao , Enze Xie , Lanqing Hong , Zhenguo Li , Gim Hee Lee

Linguistic style is an essential part of written communication, with the power to affect both clarity and attractiveness. With recent advances in vision and language, we can start to tackle the problem of generating image captions that are…

Computer Vision and Pattern Recognition · Computer Science 2018-05-21 Alexander Mathews , Lexing Xie , Xuming He

Text animation serves as an expressive medium, transforming static communication into dynamic experiences by infusing words with motion to evoke emotions, emphasize meanings, and construct compelling narratives. Crafting animations that are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Zichen Liu , Yihao Meng , Hao Ouyang , Yue Yu , Bolin Zhao , Daniel Cohen-Or , Huamin Qu
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