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While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation. In response, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yuhan Li , Yishun Dou , Yue Shi , Yu Lei , Xuanhong Chen , Yi Zhang , Peng Zhou , Bingbing Ni

Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided image editing. While text guidance is an intuitive editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jooyoung Choi , Yunjey Choi , Yunji Kim , Junho Kim , Sungroh Yoon

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

Text-based 2D image editing models have recently reached an impressive level of maturity, motivating a growing body of work that heavily depends on these models to drive 3D edits. While effective for appearance-based modifications, such…

Graphics · Computer Science 2026-04-30 Etai Sella , Hao Phung , Nitay Amiel , Or Litany , Or Patashnik , Hadar Averbuch-Elor

3D editing has shown remarkable capability in editing scenes based on various instructions. However, existing methods struggle with achieving intuitive, localized editing, such as selectively making flowers blossom. Drag-style editing has…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Chenghao Gu , Zhenzhe Li , Zhengqi Zhang , Yunpeng Bai , Shuzhao Xie , Zhi Wang

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

3D content creation via text-driven stylization has played a fundamental challenge to multimedia and graphics community. Recent advances of cross-modal foundation models (e.g., CLIP) have made this problem feasible. Those approaches…

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

While neural fields have made significant strides in view synthesis and scene reconstruction, editing them poses a formidable challenge due to their implicit encoding of geometry and texture information from multi-view inputs. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Umar Khalid , Hasan Iqbal , Nazmul Karim , Jing Hua , Chen Chen

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

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

We propose a new view synthesis method via synthesizing a 3D neural field from both single or few-view input images. To address the ill-posed nature of the image-to-3D generation problem, we devise a two-stage method that involves a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Tung Do , Thuan Hoang Nguyen , Anh Tuan Tran , Rang Nguyen , Binh-Son Hua

Although 3D object editing has the potential to significantly influence various industries, recent research in 3D generation and editing has primarily focused on converting text and images into 3D models, often overlooking the need for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 JiangDong Miao , Tatsuya Ikeda , Bisser Raytchev , Ryota Mizoguchi , Takenori Hiraoka , Takuji Nakashima , Keigo Shimizu , Toru Higaki , Kazufumi Kaneda

Recent advances in training-free attention control methods have enabled flexible and efficient text-guided editing capabilities for existing generation models. However, current approaches struggle to simultaneously deliver strong editing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Zixin Yin , Ling-Hao Chen , Lionel Ni , Xili Dai

Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

Instruction-based image editing enables precise modifications via natural language prompts, but existing methods face a precision-efficiency tradeoff: fine-tuning demands massive datasets (>10M) and computational resources, while…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Zechuan Zhang , Ji Xie , Yu Lu , Zongxin Yang , Yi Yang

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 advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yuhao Liu , Tengfei Wang , Fang Liu , Zhenwei Wang , Rynson W. H. Lau

Language-driven 3D Gaussian Splatting (3DGS) editing provides a more convenient approach for modifying complex scenes in VR/AR. Standard pipelines typically adopt a two-stage strategy: first editing multiple 2D views, and then optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yanhui Chen , Jiahong Li , Jingchao Wang , Junyi Lin , Zixin Zeng , Yang Shi

Inversion-based visual editing provides an effective and training-free way to edit an image or a video based on user instructions. Existing methods typically inject source image information during the sampling process to maintain editing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Zhi Ouyang , Dian Zheng , Xiao-Ming Wu , Jian-Jian Jiang , Kun-Yu Lin , Jingke Meng , Wei-Shi Zheng

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