English
Related papers

Related papers: GaussianEditor: Editing 3D Gaussians Delicately wi…

200 papers

We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility. The proposed approach leverages an implicit function representation of 3D human heads,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Yushi Lan , Feitong Tan , Di Qiu , Qiangeng Xu , Kyle Genova , Zeng Huang , Sean Fanello , Rohit Pandey , Thomas Funkhouser , Chen Change Loy , Yinda Zhang

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Indirect editing methods for 3D Gaussian Splatting (3DGS) have recently witnessed significant advancements. These approaches operate by first applying edits in the rendered 2D space and subsequently projecting the modifications back into…

Graphics · Computer Science 2026-03-16 Hao Qin , Yukai Sun , Meng Wang , Ming Kong , Mengxu Lu , Qiang Zhu

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Recently many techniques have emerged to create high quality 3D assets and scenes. When it comes to editing of these objects, however, existing approaches are either slow, compromise on quality, or do not provide enough customization. We…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Vishnu Jaganathan , Hannah Hanyun Huang , Muhammad Zubair Irshad , Varun Jampani , Amit Raj , Zsolt Kira

Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified appearance and location of the editing result due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Jingyu Zhuang , Di Kang , Yan-Pei Cao , Guanbin Li , Liang Lin , Ying Shan

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

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

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

The success of image generative models has enabled us to build methods that can edit images based on text or other user input. However, these methods are bespoke, imprecise, require additional information, or are limited to only 2D image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Rahul Sajnani , Jeroen Vanbaar , Jie Min , Kapil Katyal , Srinath Sridhar

We introduce 3DEgo to address a novel problem of directly synthesizing photorealistic 3D scenes from monocular videos guided by textual prompts. Conventional methods construct a text-conditioned 3D scene through a three-stage process,…

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

Recent developments in 3D reconstruction and neural rendering have significantly propelled the capabilities of photo-realistic 3D scene rendering across various academic and industrial fields. The 3D Gaussian Splatting technique, alongside…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zexu Huang , Min Xu , Stuart Perry

We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a scene and the collection of images used to reconstruct it, our method uses an image-conditioned diffusion model (InstructPix2Pix) to iteratively edit the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Ayaan Haque , Matthew Tancik , Alexei A. Efros , Aleksander Holynski , Angjoo Kanazawa

Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently often produce geometrically and photometrically inconsistent results across different views of the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Josef Bengtson , David Nilsson , Dong In Lee , Yaroslava Lochman , Fredrik Kahl

Recent text-guided generation of individual 3D object has achieved great success using diffusion priors. However, these methods are not suitable for object insertion and replacement tasks as they do not consider the background, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Hanyuan Xiao , Yingshu Chen , Huajian Huang , Haolin Xiong , Jing Yang , Pratusha Prasad , Yajie Zhao

Neural Radiance Fields achieve high-fidelity scene representation but suffer from costly training and rendering, while 3D Gaussian splatting offers real-time performance with strong empirical results. Recently, solutions that harness the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Grzegorz Wilczyński , Mikołaj Zieliński , Krzysztof Byrski , Joanna Waczyńska , Dominik Belter , Przemysław Spurek

3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometric priors. Existing methods have explored predicting point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Kanle Shi , Shenkun Xu , Yi Fang , Yu-Shen Liu

The advancement of text-driven 3D content editing has been blessed by the progress from 2D generative diffusion models. However, a major obstacle hindering the widespread adoption of 3D content editing is its time-intensive processing. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Liangchen Song , Liangliang Cao , Jiatao Gu , Yifan Jiang , Junsong Yuan , Hao Tang

With the widespread application of 3D Gaussians in 3D scene representation, 3D scene segmentation methods based on 3D Gaussians have also gradually emerged. However, existing 3D Gaussian segmentation methods basically segment on the basis…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Liwei Liao , Ronggang Wang