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Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusion models gradually synthesize images in an iterative fashion…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Yogesh Balaji , Seungjun Nah , Xun Huang , Arash Vahdat , Jiaming Song , Qinsheng Zhang , Karsten Kreis , Miika Aittala , Timo Aila , Samuli Laine , Bryan Catanzaro , Tero Karras , Ming-Yu Liu

We present a simple but effective training-free approach for text-driven image-to-image translation based on a pretrained text-to-image diffusion model. Our goal is to generate an image that aligns with the target task while preserving the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Hyunsoo Lee , Minsoo Kang , Bohyung Han

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Editing real images using a pre-trained text-to-image (T2I) diffusion/flow model often involves inverting the image into its corresponding noise map. However, inversion by itself is typically insufficient for obtaining satisfactory results,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Vladimir Kulikov , Matan Kleiner , Inbar Huberman-Spiegelglas , Tomer Michaeli

Recent advances in diffusion models have significantly improved image generation and editing, but extending these capabilities to 3D assets remains challenging, especially for fine-grained edits that require multi-view consistency. Existing…

Graphics · Computer Science 2025-07-01 Junchao Huang , Xinting Hu , Shaoshuai Shi , Zhuotao Tian , Li Jiang

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

Visual-prompt-guided edit transfer aims to learn image transformations directly from example pairs, offering more precise and controllable editing than purely text-driven approaches. However, existing diffusion transformer-based methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Lan Chen , Qi Mao , Yiren Song , Yuchao Gu , Siwei Ma

Recently large-scale language-image models (e.g., text-guided diffusion models) have considerably improved the image generation capabilities to generate photorealistic images in various domains. Based on this success, current image editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Wenkai Dong , Song Xue , Xiaoyue Duan , Shumin Han

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Recently, text-to-image (T2I) editing has been greatly pushed forward by applying diffusion models. Despite the visual promise of the generated images, inconsistencies with the expected textual prompt remain prevalent. This paper aims to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Aoxue Li , Mingyang Yi , Zhenguo Li

The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional challenges in the time dimension, image editing has witnessed the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Wenqi Ouyang , Yi Dong , Lei Yang , Jianlou Si , Xingang Pan

A precise and user-friendly manipulation of image content while preserving image fidelity has always been crucial to the field of image editing. Thanks to the power of generative models, recent point-based image editing methods allow users…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Minxing Luo , Wentao Cheng , Jian Yang

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

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

Diffusion models have opened the path to a wide range of text-based image editing frameworks. However, these typically build on the multi-step nature of the diffusion backwards process, and adapting them to distilled, fast-sampling methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Gilad Deutch , Rinon Gal , Daniel Garibi , Or Patashnik , Daniel Cohen-Or

With the rise of large, publicly-available text-to-image diffusion models, text-guided real image editing has garnered much research attention recently. Existing methods tend to either rely on some form of per-instance or per-task…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Adham Elarabawy , Harish Kamath , Samuel Denton

Large-scale text-to-image diffusion models have been a ground-breaking development in generating convincing images following an input text prompt. The goal of image editing research is to give users control over the generated images by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Chuanming Tang , Kai Wang , Joost van de Weijer

Recent years have witnessed significant advancements in text-guided style transfer, primarily attributed to innovations in diffusion models. These models excel in conditional guidance, utilizing text or images to direct the sampling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Nisha Huang , Kaer Huang , Yifan Pu , Jiangshan Wang , Jie Guo , Yiqiang Yan , Xiu Li , Tong-Yee Lee

Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de facto method for performing edits with T2I models is through text instructions,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Ashutosh Srivastava , Tarun Ram Menta , Abhinav Java , Avadhoot Jadhav , Silky Singh , Surgan Jandial , Balaji Krishnamurthy

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao