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3D Gaussian Splatting has recently enabled fast and photorealistic reconstruction of static 3D scenes. However, dynamic editing of such scenes remains a significant challenge. We introduce a novel framework, Physics-Guided Score…

Graphics · Computer Science 2026-03-26 Gal Fiebelman , Hadar Averbuch-Elor , Sagie Benaim

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jiatao Gu , Qingzhe Gao , Shuangfei Zhai , Baoquan Chen , Lingjie Liu , Josh Susskind

Text-based generation and editing of 3D scenes hold significant potential for streamlining content creation through intuitive user interactions. While recent advances leverage 3D Gaussian Splatting (3DGS) for high-fidelity and real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Hyojun Go , Byeongjun Park , Jiho Jang , Jin-Young Kim , Soonwoo Kwon , Changick Kim

We present a method to generate 3D objects in styles. Our method takes a text prompt and a style reference image as input and reconstructs a neural radiance field to synthesize a 3D model with the content aligning with the text prompt and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Hubert Kompanowski , Binh-Son Hua

Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differentiable 3D representations. However, the approaches often suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ming He , Zhixiang Chen , Steve Maddock

Diffusion models achieve high-quality image generation but are limited by slow iterative sampling. Distillation methods alleviate this by enabling one- or few-step generation. Flow matching, originally introduced as a distinct framework,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Mingyuan Zhou , Yi Gu , Huangjie Zheng , Liangchen Song , Guande He , Yizhe Zhang , Wenze Hu , Yinfei Yang

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

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

The advent of 3D Gaussian Splatting (3DGS) has revolutionized 3D editing, offering efficient, high-fidelity rendering and enabling precise local manipulations. Currently, diffusion-based 2D editing models are harnessed to modify multi-view…

Graphics · Computer Science 2025-02-18 Yuxuan Wang , Xuanyu Yi , Zike Wu , Na Zhao , Long Chen , Hanwang Zhang

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

The stylization of 3D scenes is an increasingly attractive topic in 3D vision. Although image style transfer has been extensively researched with promising results, directly applying 2D style transfer methods to 3D scenes often fails to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yushen Zuo , Jun Xiao , Kin-Chung Chan , Rongkang Dong , Cuixin Yang , Zongqi He , Hao Xie , Kin-Man Lam

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

Score distillation sampling (SDS) has shown great promise in text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models, but suffers from over-saturation, over-smoothing, and low-diversity problems. In this…

Machine Learning · Computer Science 2023-11-23 Zhengyi Wang , Cheng Lu , Yikai Wang , Fan Bao , Chongxuan Li , Hang Su , Jun Zhu

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance from pre-trained diffusion models. An apparent drawback is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yiji Cheng , Fei Yin , Xiaoke Huang , Xintong Yu , Jiaxiang Liu , Shikun Feng , Yujiu Yang , Yansong Tang

3D Gaussian Splatting (3DGS) has recently emerged as a fast, high-quality method for novel view synthesis (NVS). However, its use of low-degree spherical harmonics limits its ability to capture spatially varying color and view-dependent…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

Score distillation sampling (SDS), the methodology in which the score from pretrained 2D diffusion models is distilled into 3D representation, has recently brought significant advancements in text-to-3D generation task. However, this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Min-Seop Kwak , Donghoon Ahn , Ines Hyeonsu Kim , Jin-Hwa Kim , Seungryong Kim

Despite the impressive results of arbitrary image-guided style transfer methods, text-driven image stylization has recently been proposed for transferring a natural image into a stylized one according to textual descriptions of the target…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Nisha Huang , Yuxin Zhang , Fan Tang , Chongyang Ma , Haibin Huang , Yong Zhang , Weiming Dong , Changsheng Xu

The advent of 3D Gaussian Splatting (3DGS) has advanced 3D scene reconstruction and novel view synthesis. With the growing interest of interactive applications that need immediate feedback, online 3DGS reconstruction in real-time is in high…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yang LI , Jinglu Wang , Lei Chu , Xiao Li , Shiu-hong Kao , Ying-Cong Chen , Yan Lu

Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Junyoung Seo , Wooseok Jang , Min-Seop Kwak , Hyeonsu Kim , Jaehoon Ko , Junho Kim , Jin-Hwa Kim , Jiyoung Lee , Seungryong Kim