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Related papers: Creative Image Generation with Diffusion Models

200 papers

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

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren

Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps. Despite their good performance, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Noam Elata , Bahjat Kawar , Tomer Michaeli , Michael Elad

While diffusion models have shown great success in image generation, their noise-inverting generative process does not explicitly consider the structure of images, such as their inherent multi-scale nature. Inspired by diffusion models and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Severi Rissanen , Markus Heinonen , Arno Solin

Diffusion models have become the go-to method for many generative tasks, particularly for image-to-image generation tasks such as super-resolution and inpainting. Current diffusion-based methods do not provide statistical guarantees…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Eliahu Horwitz , Yedid Hoshen

The recent wave of large-scale text-to-image diffusion models has dramatically increased our text-based image generation abilities. These models can generate realistic images for a staggering variety of prompts and exhibit impressive…

Machine Learning · Computer Science 2023-09-14 Alexander C. Li , Mihir Prabhudesai , Shivam Duggal , Ellis Brown , Deepak Pathak

Generative models have enabled intuitive image creation and manipulation using natural language. In particular, diffusion models have recently shown remarkable results for natural image editing. In this work, we propose to apply diffusion…

Have you ever thought that you can be an intelligent painter? This means that you can paint a picture with a few expected objects in mind, or with a desirable scene. This is different from normal inpainting approaches for which the location…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Wing-Fung Ku , Wan-Chi Siu , Xi Cheng , H. Anthony Chan

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

Diffusion-based models have gained significant popularity for text-to-image generation due to their exceptional image-generation capabilities. A risk with these models is the potential generation of inappropriate content, such as biased or…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Hang Li , Chengzhi Shen , Philip Torr , Volker Tresp , Jindong Gu

We introduce a novel approach for concept blending in pretrained text-to-image diffusion models, aiming to generate images at the intersection of multiple text prompts. At each time step during diffusion denoising, our algorithm forecasts…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Divya Kothandaraman , Ming Lin , Dinesh Manocha

Text-to-image models are powerful tools for image creation. However, the generation process is akin to a dice roll and makes it difficult to achieve a single image that captures everything a user wants. In this paper, we propose a framework…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Sean J. Liu , Nupur Kumari , Ariel Shamir , Jun-Yan Zhu

Denoising diffusion probabilistic models are a promising new class of generative models that mark a milestone in high-quality image generation. This paper showcases their ability to sequentially generate video, surpassing prior methods in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Ruihan Yang , Prakhar Srivastava , Stephan Mandt

Recent advancements in large scale text-to-image models have opened new possibilities for guiding the creation of images through human-devised natural language. However, while prior literature has primarily focused on the generation of…

Computer Vision and Pattern Recognition · Computer Science 2023-02-09 Hyeonho Jeong , Gihyun Kwon , Jong Chul Ye

Creative visual concept generation often draws inspiration from specific concepts in a reference image to produce relevant outcomes. However, existing methods are typically constrained to single-aspect concept generation or are easily…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Yangyang Li , Daqing Liu , Wu Liu , Allen He , Xinchen Liu , Yongdong Zhang , Guoqing Jin

We propose a text-to-image generation algorithm based on deep neural networks when text captions for images are unavailable during training. In this work, instead of simply generating pseudo-ground-truth sentences of training images using…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Minsoo Kang , Doyup Lee , Jiseob Kim , Saehoon Kim , Bohyung Han

Image tiling -- the seamless connection of disparate images to create a coherent visual field -- is crucial for applications such as texture creation, video game asset development, and digital art. Traditionally, tiles have been constructed…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Or Madar , Ohad Fried

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

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

Diffusion-based generative models are a design framework that allows generating new images from processes analogous to those found in non-equilibrium thermodynamics. These models model the reversal of a physical diffusion process in which…

Artificial Intelligence · Computer Science 2023-02-21 Jordi de la Torre