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We propose a novel image-to-pencil translation method that could not only generate high-quality pencil sketches but also offer the drawing process. Existing pencil sketch algorithms are based on texture rendering rather than the direct…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Zhengyan Tong , Xuanhong Chen , Bingbing Ni , Xiaohang Wang

Oil painting, as a high-level medium that blends human abstract thinking with artistic expression, poses substantial challenges for digital generation and editing due to its intricate brushstroke dynamics and stylized characteristics.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Zhangli Hu , Ye Chen , Jiajun Yao , Bingbing Ni

Artistic Glyph Image Generation (AGIG) differs from current creativity-focused generation models by offering finely controllable deterministic generation. It transfers the style of a reference image to a source while preserving its content.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiongbo Lu , Yaxiong Chen , Shengwu Xiong

Text-guided image generation aimed to generate desired images conditioned on given texts, while text-guided image manipulation refers to semantically edit parts of a given image based on specified texts. For these two similar tasks, the key…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Xiaozhou You , Jian Zhang

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Text-driven video editing utilizing generative diffusion models has garnered significant attention due to their potential applications. However, existing approaches are constrained by the limited word embeddings provided in pre-training,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Mingce Guo , Jingxuan He , Shengeng Tang , Zhangye Wang , Lechao Cheng

Recent advancements in autoregressive and diffusion models have led to strong performance in image generation with short scene text words. However, generating coherent, long-form text in images, such as paragraphs in slides or documents,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Alex Jinpeng Wang , Linjie Li , Zhengyuan Yang , Lijuan Wang , Min Li

Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent progress has been made in text-to-image generation, text-to-shape generation remains a challenging problem…

Computer Vision and Pattern Recognition · Computer Science 2022-05-02 Aditya Sanghi , Hang Chu , Joseph G. Lambourne , Ye Wang , Chin-Yi Cheng , Marco Fumero , Kamal Rahimi Malekshan

Although contemporary text-to-image generation models have achieved remarkable breakthroughs in producing visually appealing images, their capacity to generate precise and flexible typographic elements, especially non-Latin alphabets,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Haofan Wang , Yujia Xu , Yimeng Li , Junchen Li , Chaowei Zhang , Jing Wang , Kejia Yang , Zhibo Chen

In order to offer a customized script tool and inspire professional scriptwriters, we present VScript. It is a controllable pipeline that generates complete scripts, including dialogues and scene descriptions, as well as presents visually…

Computation and Language · Computer Science 2022-11-24 Ziwei Ji , Yan Xu , I-Tsun Cheng , Samuel Cahyawijaya , Rita Frieske , Etsuko Ishii , Min Zeng , Andrea Madotto , Pascale Fung

Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability. This work offers a new generation paradigm that allows flexible control of the output image,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-23 Lianghua Huang , Di Chen , Yu Liu , Yujun Shen , Deli Zhao , Jingren Zhou

Neural controllable text generation is an important area gaining attention due to its plethora of applications. Although there is a large body of prior work in controllable text generation, there is no unifying theme. In this work, we…

Computation and Language · Computer Science 2020-11-03 Shrimai Prabhumoye , Alan W Black , Ruslan Salakhutdinov

Neural style transfer is a powerful computer vision technique that can incorporate the artistic "style" of one image to the "content" of another. The underlying theory behind the approach relies on the assumption that the style of an image…

Machine Learning · Computer Science 2022-09-26 Yousef El-Laham , Svitlana Vyetrenko

Advanced image fusion methods are devoted to generating the fusion results by aggregating the complementary information conveyed by the source images. However, the difference in the source-specific manifestation of the imaged scene content…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Chunyang Cheng , Tianyang Xu , Xiao-Jun Wu , Hui Li , Xi Li , Zhangyong Tang , Josef Kittler

Stylistic text generation plays a vital role in enhancing communication by reflecting the nuances of individual expression. This paper presents a novel approach for generating text in a specific speaker's style across different languages.…

Computation and Language · Computer Science 2025-01-23 Karishma Thakrar , Katrina Lawrence , Kyle Howard

Artistic style transfer is an image synthesis problem where the content of an image is reproduced with the style of another. Recent works show that a visually appealing style transfer can be achieved by using the hidden activations of a…

Computer Vision and Pattern Recognition · Computer Science 2016-12-14 Tian Qi Chen , Mark Schmidt

Prior work in style-controlled text generation has focused on tasks such as emulating the style of prolific literary authors, producing formal or informal text, and mitigating toxicity of generated text. Plentiful demonstrations of these…

Computation and Language · Computer Science 2024-03-05 Aleem Khan , Andrew Wang , Sophia Hager , Nicholas Andrews

We present a method for zero-shot, text-driven appearance manipulation in natural images and videos. Given an input image or video and a target text prompt, our goal is to edit the appearance of existing objects (e.g., object's texture) or…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Omer Bar-Tal , Dolev Ofri-Amar , Rafail Fridman , Yoni Kasten , Tali Dekel

Leveraging large-scale image-text datasets and advancements in diffusion models, text-driven generative models have made remarkable strides in the field of image generation and editing. This study explores the potential of extending the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Fu-Yun Wang , Wenshuo Chen , Guanglu Song , Han-Jia Ye , Yu Liu , Hongsheng Li

Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world. In spite of such advances, a higher level understanding of vision and imagery…

Computer Vision and Pattern Recognition · Computer Science 2019-04-05 Raphael Gontijo Lopes , David Ha , Douglas Eck , Jonathon Shlens