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Related papers: Plasticine3D: 3D Non-Rigid Editing with Text Guida…

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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

Recent video editing methods achieve attractive results in style transfer or appearance modification. However, editing the structural content of 3D scenes in videos remains challenging, particularly when dealing with significant viewpoint…

Graphics · Computer Science 2025-08-20 Feng-Lin Liu , Shi-Yang Li , Yan-Pei Cao , Hongbo Fu , Lin Gao

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

Instruction-based image editing models have recently achieved impressive performance, enabling complex edits to an input image from a multi-instruction prompt. However, these models apply each instruction in the prompt with a fixed…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Arman Zarei , Samyadeep Basu , Mobina Pournemat , Sayan Nag , Ryan Rossi , Soheil Feizi

Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity. To bridge this gap, recent works have investigated multi-view diffusion but often fall short in either 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hansheng Chen , Ruoxi Shi , Yulin Liu , Bokui Shen , Jiayuan Gu , Gordon Wetzstein , Hao Su , Leonidas Guibas

3D editing refers to the ability to apply local or global modifications to 3D assets. Effective 3D editing requires maintaining semantic consistency by performing localized changes according to prompts, while also preserving local…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Yizhao Xu , Hongyuan Zhu , Caiyun Liu , Tianfu Wang , Keyu Chen , Sicheng Xu , Jiaolong Yang , Nicholas Jing Yuan , Qi Zhang

We address the task of multi-view image editing from sparse input views, where the inputs can be seen as a mix of images capturing the scene from different viewpoints. The goal is to modify the scene according to a textual instruction while…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Daniel Gilo , Or Litany

This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Jun-Kun Chen , Yu-Xiong Wang

Novel view synthesis under sparse views has been a long-term important challenge in 3D reconstruction. Existing works mainly rely on introducing external semantic or depth priors to supervise the optimization of 3D representations. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Qisen Wang , Yifan Zhao , Jiawei Ma , Jia Li

While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains challenging, particularly in maintaining multi-view consistency. Classical approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufeng Chi , Huimin Ma , Kafeng Wang , Jianmin Li

Diffusion-based image editing is a composite process of preserving the source image content and generating new content or applying modifications. While current editing approaches have made improvements under text guidance, most of them have…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Tianrui Huang , Pu Cao , Lu Yang , Chun Liu , Mengjie Hu , Zhiwei Liu , Qing Song

This paper introduces V$^2$Edit, a novel training-free framework for instruction-guided video and 3D scene editing. Addressing the critical challenge of balancing original content preservation with editing task fulfillment, our approach…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Yanming Zhang , Jun-Kun Chen , Jipeng Lyu , Yu-Xiong Wang

Text-guided non-rigid editing involves complex edits for input images, such as changing motion or compositions within their surroundings. Since it requires manipulating the input structure, existing methods often struggle with preserving…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Yunji Jung , Seokju Lee , Tair Djanibekov , Hyunjung Shim , Jong Chul Ye

Score Distillation Sampling (SDS) leverages pretrained 2D diffusion models to advance text-to-3D generation but neglects multi-view correlations, being prone to geometric inconsistencies and multi-face artifacts in the generated 3D content.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Feng Yang , Wenliang Qian , Wangmeng Zuo , Hui Li

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

We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS and edits them by using a pre-trained 2D diffusion model…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jing Wu , Jia-Wang Bian , Xinghui Li , Guangrun Wang , Ian Reid , Philip Torr , Victor Adrian Prisacariu

Score Distillation Sampling (SDS) has emerged as a prominent method for text-to-3D generation by leveraging the strengths of 2D diffusion models. However, SDS is limited to generation tasks and lacks the capability to edit existing 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Xingyu Miao , Haoran Duan , Yang Long , Jungong Han

Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's identity when users make large edits. We propose a one-shot…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Yuta Okuyama , Yuki Endo , Yoshihiro Kanamori

This paper introduces a new approach based on a coupled representation and a neural volume optimization to implicitly perform 3D shape editing in latent space. This work has three innovations. First, we design the coupled neural shape (CNS)…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Jingyu Hu , Ka-Hei Hui , Zhengzhe Liu , Hao Zhang , Chi-Wing Fu