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Drag-based editing allows precise object manipulation through point-based control, offering user convenience. However, current methods often suffer from a geometric inconsistency problem by focusing exclusively on matching user-defined…

Graphics · Computer Science 2025-07-14 Gwanhyeong Koo , Sunjae Yoon , Younghwan Lee , Ji Woo Hong , Chang D. Yoo

The transformative potential of 3D content creation has been progressively unlocked through advancements in generative models. Recently, intuitive drag editing with geometric changes has attracted significant attention in 2D editing yet…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Jiahua Dong , Yu-Xiong Wang

To serve the intricate and varied demands of image editing, precise and flexible manipulation in image content is indispensable. Recently, Drag-based editing methods have gained impressive performance. However, these methods predominantly…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Pengyang Ling , Lin Chen , Pan Zhang , Huaian Chen , Yi Jin , Jinjin Zheng

Drag-based image editing has emerged as a powerful paradigm for intuitive image manipulation. However, existing approaches predominantly rely on manipulating the latent space of generative models, leading to limited precision, delayed…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Jingyi Lu , Kai Han

Point-drag-based image editing methods, like DragDiffusion, have attracted significant attention. However, point-drag-based approaches suffer from computational overhead and misinterpretation of user intentions due to the sparsity of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Jingyi Lu , Xinghui Li , Kai Han

To achieve pixel-level image manipulation, drag-style image editing which edits images using points or trajectories as conditions is attracting widespread attention. Most previous methods follow move-and-track framework, in which miss…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Jiacheng Sui , Yujie Zhou , Li Niu

Drag-based image editing using generative models provides intuitive control over image structures. However, existing methods rely heavily on manually provided masks and textual prompts to preserve semantic fidelity and motion precision.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Sheng-Hao Liao , Shang-Fu Chen , Tai-Ming Huang , Wen-Huang Cheng , Kai-Lung Hua

Precise and flexible image editing remains a fundamental challenge in computer vision. Based on the modified areas, most editing methods can be divided into two main types: global editing and local editing. In this paper, we choose the two…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Ziqi Jiang , Zhen Wang , Long Chen

Precise geometric control in image generation is essential for engineering \& product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Phillip Mueller , Talip Uenlue , Sebastian Schmidt , Marcel Kollovieh , Jiajie Fan , Stephan Guennemann , Lars Mikelsons

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

Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, each of these methods has inherent limitations: text-based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Haoran Yu , Yi Shi

Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guided editing on 3D representations, such as 3D Gaussian…

Graphics · Computer Science 2025-05-27 Yansong Qu , Dian Chen , Xinyang Li , Xiaofan Li , Shengchuan Zhang , Liujuan Cao , Rongrong Ji

Drag-based image editing has recently gained popularity for its interactivity and precision. However, despite the ability of text-to-image models to generate samples within a second, drag editing still lags behind due to the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Joonghyuk Shin , Daehyeon Choi , Jaesik Park

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Point-based image editing has attracted remarkable attention since the emergence of DragGAN. Recently, DragDiffusion further pushes forward the generative quality via adapting this dragging technique to diffusion models. Despite these great…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Yutao Cui , Xiaotong Zhao , Guozhen Zhang , Shengming Cao , Kai Ma , Limin Wang

Towards intelligent image editing, object removal should eliminate both the target object and its causal visual artifacts, such as shadows and reflections. However, existing image appearance-based methods either follow strictly mask-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Zixin Zhu , Haoxiang Li , Xuelu Feng , He Wu , Chunming Qiao , Junsong Yuan

Image editing has made great progress on planar images, but panoramic image editing remains underexplored. Due to their spherical geometry and projection distortions, panoramic images present three key challenges: boundary discontinuity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Zhiao Feng , Xuewei Li , Junjie Yang , Jingchao Li , Yuxin Peng , Xi Li

Generative models have achieved significant progress in advancing 2D image editing, demonstrating exceptional precision and realism. However, they often struggle with consistency and object identity preservation due to their inherent…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuhuan Xie , Aoxuan Pan , Ming-Xian Lin , Wei Huang , Yi-Hua Huang , Xiaojuan Qi

We present Image Sculpting, a new framework for editing 2D images by incorporating tools from 3D geometry and graphics. This approach differs markedly from existing methods, which are confined to 2D spaces and typically rely on textual…

Graphics · Computer Science 2024-01-04 Jiraphon Yenphraphai , Xichen Pan , Sainan Liu , Daniele Panozzo , Saining Xie

This paper explores image editing under the joint control of text and drag interactions. While recent advances in text-driven and drag-driven editing have achieved remarkable progress, they suffer from complementary limitations: text-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Qihang Wang , Yaxiong Wang , Lechao Cheng , Zhun Zhong
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