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Large-scale text-to-image generative models have shown their remarkable ability to synthesize diverse and high-quality images. However, it is still challenging to directly apply these models for editing real images for two reasons. First,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Gaurav Parmar , Krishna Kumar Singh , Richard Zhang , Yijun Li , Jingwan Lu , Jun-Yan Zhu

In this work we combine two research threads from Vision/ Graphics and Natural Language Processing to formulate an image generation task conditioned on attributes in a multi-turn setting. By multiturn, we mean the image is generated in a…

Computer Vision and Pattern Recognition · Computer Science 2018-06-19 Ryan Y. Benmalek , Claire Cardie , Serge Belongie , Xiadong He , Jianfeng Gao

Vector graphics are widely used in digital art and valued by designers for their scalability and layer-wise topological properties. However, the creation and editing of vector graphics necessitate creativity and design expertise, leading to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Peiying Zhang , Nanxuan Zhao , Jing Liao

Despite significant advancements in image customization with diffusion models, current methods still have several limitations: 1) unintended changes in non-target areas when regenerating the entire image; 2) guidance solely by a reference…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Pengzhi Li , Qiang Nie , Ying Chen , Xi Jiang , Kai Wu , Yuhuan Lin , Yong Liu , Jinlong Peng , Chengjie Wang , Feng Zheng

Text-guided image editing involves modifying a source image based on a language instruction and, typically, requires changes to only small local regions. However, existing approaches generate the entire target image rather than selectively…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Huimin Wu , Xiaojian Ma , Haozhe Zhao , Yanpeng Zhao , Qing Li

Recent advances in diffusion models have enabled high-quality generation and manipulation of images guided by texts, as well as concept learning from images. However, naive applications of existing methods to editing tasks that require…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xudong Liu , Zikun Chen , Ruowei Jiang , Ziyi Wu , Kejia Yin , Han Zhao , Parham Aarabi , Igor Gilitschenski

Many real-world applications, such as interactive photo retouching, artistic content creation, and product design, require flexible and iterative image editing. However, existing image editing methods primarily focus on achieving the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Zijun Zhou , Yingying Deng , Xiangyu He , Weiming Dong , Fan Tang

This paper introduces an innovative methodology for producing high-quality 3D lung CT images guided by textual information. While diffusion-based generative models are increasingly used in medical imaging, current state-of-the-art…

Image and Video Processing · Electrical Eng. & Systems 2024-10-16 Yanwu Xu , Li Sun , Wei Peng , Shuyue Jia , Katelyn Morrison , Adam Perer , Afrooz Zandifar , Shyam Visweswaran , Motahhare Eslami , Kayhan Batmanghelich

Recent advances in deep generative models have demonstrated impressive results in photo-realistic facial image synthesis and editing. Facial expressions are inherently the result of muscle movement. However, existing neural network-based…

Computer Vision and Pattern Recognition · Computer Science 2019-11-07 ShahRukh Athar , Zhixin Shu , Dimitris Samaras

Images as an artistic medium often rely on specific camera angles and lens distortions to convey ideas or emotions; however, such precise control is missing in current text-to-image models. We propose an efficient and general solution that…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Edurne Bernal-Berdun , Ana Serrano , Belen Masia , Matheus Gadelha , Yannick Hold-Geoffroy , Xin Sun , Diego Gutierrez

Realistic image manipulation is challenging because it requires modifying the image appearance in a user-controlled way, while preserving the realism of the result. Unless the user has considerable artistic skill, it is easy to "fall off"…

Computer Vision and Pattern Recognition · Computer Science 2018-12-18 Jun-Yan Zhu , Philipp Krähenbühl , Eli Shechtman , Alexei A. Efros

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Recent text-to-image generation models have demonstrated impressive capability of generating text-aligned images with high fidelity. However, generating images of novel concept provided by the user input image is still a challenging task.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yufan Zhou , Ruiyi Zhang , Tong Sun , Jinhui Xu

Recent advances in diffusion-based generative models have shown incredible promise for zero shot image-to-image translation and editing. Most of these approaches work by combining or replacing network-specific features used in the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Zeqi Gu , Ethan Yang , Abe Davis

Sketch-based image editing aims to synthesize and modify photos based on the structural information provided by the human-drawn sketches. Since sketches are difficult to collect, previous methods mainly use edge maps instead of sketches to…

Computer Vision and Pattern Recognition · Computer Science 2020-01-10 Shuai Yang , Zhangyang Wang , Jiaying Liu , Zongming Guo

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

Diffusion models have recently been shown to generate high-quality synthetic images, especially when paired with a guidance technique to trade off diversity for fidelity. We explore diffusion models for the problem of text-conditional image…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Alex Nichol , Prafulla Dhariwal , Aditya Ramesh , Pranav Shyam , Pamela Mishkin , Bob McGrew , Ilya Sutskever , Mark Chen

We propose a training-free approach to 3D editing that enables the editing of a single shape within a few minutes. The edited 3D mesh aligns well with the prompts, and remains identical for regions that are not intended to be altered. To…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziya Erkoç , Can Gümeli , Chaoyang Wang , Matthias Nießner , Angela Dai , Peter Wonka , Hsin-Ying Lee , Peiye Zhuang

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

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

Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control signals, such as contextual descriptions, and rarely supports bold geometric distortions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Changwoon Choi , Hyunsoo Lee , Clément Jambon , Yael Vinker , Young Min Kim
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