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The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

Diffusion models have become central to various image editing tasks, yet they often fail to fully adhere to physical laws, particularly with effects like shadows, reflections, and occlusions. In this work, we address the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Ankit Dhiman , Manan Shah , R Venkatesh Babu

Automatic font generation without human experts is a practical and significant problem, especially for some languages that consist of a large number of characters. Existing methods for font generation are often in supervised learning. They…

Computer Vision and Pattern Recognition · Computer Science 2023-01-02 Xinyuan Chen , Yangchen Xie , Li Sun , Yue Lu

Fashionable image generation aims to synthesize images of diverse fashion prevalent around the globe, helping fashion designers in real-time visualization by giving them a basic customized structure of how a specific design preference would…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Krishna Sri Ipsit Mantri , Nevasini Sasikumar

Diffusion model based Text-to-Image has achieved impressive achievements recently. Although current technology for synthesizing images is highly advanced and capable of generating images with high fidelity, it is still possible to give the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Yuxiang Tuo , Wangmeng Xiang , Jun-Yan He , Yifeng Geng , Xuansong Xie

Along the rapid development of deep learning techniques in generative models, it is becoming an urgent issue to combine machine intelligence with human intelligence to solve the practical applications. Motivated by this methodology, this…

Graphics · Computer Science 2021-06-18 Haoran Xie , Yuki Fujita , Kazunori Miyata

Text-driven person image generation is an emerging and challenging task in cross-modality image generation. Controllable person image generation promotes a wide range of applications such as digital human interaction and virtual try-on.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-14 Kaiduo Zhang , Muyi Sun , Jianxin Sun , Binghao Zhao , Kunbo Zhang , Zhenan Sun , Tieniu Tan

The quality of the prompts provided to text-to-image diffusion models determines how faithful the generated content is to the user's intent, often requiring `prompt engineering'. To harness visual concepts from target images without prompt…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Shweta Mahajan , Tanzila Rahman , Kwang Moo Yi , Leonid Sigal

Text-to-Image synthesis is the task of generating an image according to a specific text description. Generative Adversarial Networks have been considered the standard method for image synthesis virtually since their introduction. Denoising…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Konstantina Nikolaidou , George Retsinas , Vincent Christlein , Mathias Seuret , Giorgos Sfikas , Elisa Barney Smith , Hamam Mokayed , Marcus Liwicki

Diffusion models arise as a powerful generative tool recently. Despite the great progress, existing diffusion models mainly focus on uni-modal control, i.e., the diffusion process is driven by only one modality of condition. To further…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Ziqi Huang , Kelvin C. K. Chan , Yuming Jiang , Ziwei Liu

Diffusion Models are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Md Manjurul Ahsan , Shivakumar Raman , Yingtao Liu , Zahed Siddique

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

Recent advances in diffusion models have introduced a new era of text-guided image manipulation, enabling users to create realistic edited images with simple textual prompts. However, there is significant concern about the potential misuse…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 June Suk Choi , Kyungmin Lee , Jongheon Jeong , Saining Xie , Jinwoo Shin , Kimin Lee

Style transfer is an inventive process designed to create an image that maintains the essence of the original while embracing the visual style of another. Although diffusion models have demonstrated impressive generative power in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Haofan Wang , Peng Xing , Renyuan Huang , Hao Ai , Qixun Wang , Xu Bai

3D content creation via text-driven stylization has played a fundamental challenge to multimedia and graphics community. Recent advances of cross-modal foundation models (e.g., CLIP) have made this problem feasible. Those approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Tao Mei

Recently, text-guided image editing has achieved significant success. However, existing methods can only apply simple textures like wood or gold when changing the texture of an object. Complex textures such as cloud or fire pose a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Zihan Su , Junhao Zhuang , Chun Yuan

Tuning-free diffusion-based models have demonstrated significant potential in the realm of image personalization and customization. However, despite this notable progress, current models continue to grapple with several complex challenges…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Haofan Wang , Matteo Spinelli , Qixun Wang , Xu Bai , Zekui Qin , Anthony Chen

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Anomaly inspection plays an important role in industrial manufacture. Existing anomaly inspection methods are limited in their performance due to insufficient anomaly data. Although anomaly generation methods have been proposed to augment…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Teng Hu , Jiangning Zhang , Ran Yi , Yuzhen Du , Xu Chen , Liang Liu , Yabiao Wang , Chengjie Wang

Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different users usually expect different outcomes. Therefore, we propose…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Shin-I Cheng , Yu-Jie Chen , Wei-Chen Chiu , Hung-Yu Tseng , Hsin-Ying Lee
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