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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 present InstantStyleGaussian, an innovative 3D style transfer method based on the 3D Gaussian Splatting (3DGS) scene representation. By inputting a target-style image, it quickly generates new 3D GS scenes. Our method operates on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xin-Yi Yu , Jun-Xin Yu , Li-Bo Zhou , Yan Wei , Lin-Lin Ou

While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper introduces a novel 3D generation framework that addresses these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Yushi Lan , Shangchen Zhou , Zhaoyang Lyu , Fangzhou Hong , Shuai Yang , Bo Dai , Xingang Pan , Chen Change Loy

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

3D Gaussian Splatting (3DGS) enables the reconstruction of intricate digital 3D assets from multi-view images by leveraging a set of 3D Gaussian primitives for rendering. Its explicit and discrete representation facilitates the seamless…

Graphics · Computer Science 2025-05-13 Xijie Yang , Linning Xu , Lihan Jiang , Dahua Lin , Bo Dai

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

The emergence of 3D Gaussian Splatting (3D-GS) has significantly advanced 3D reconstruction by providing high fidelity and fast training speeds across various scenarios. While recent efforts have mainly focused on improving model structures…

Graphics · Computer Science 2025-03-07 Yifei Gao , Jun Huang , Lei Wang , Ruiting Dai , Jun Cheng

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, generating multiple objects with reasonable interactions within a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chongjian Ge , Chenfeng Xu , Yuanfeng Ji , Chensheng Peng , Masayoshi Tomizuka , Ping Luo , Mingyu Ding , Varun Jampani , Wei Zhan

Generating and inserting new objects into 3D content is a compelling approach for achieving versatile scene recreation. Existing methods, which rely on SDS optimization or single-view inpainting, often struggle to produce high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Hongliang Zhong , Can Wang , Jingbo Zhang , Jing Liao

Recently, 3D Gaussian splatting (3D-GS) has achieved great success in reconstructing and rendering real-world scenes. To transfer the high rendering quality to generation tasks, a series of research works attempt to generate 3D-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Taoran Yi , Jiemin Fang , Zanwei Zhou , Junjie Wang , Guanjun Wu , Lingxi Xie , Xiaopeng Zhang , Wenyu Liu , Xinggang Wang , Qi Tian

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate the initial layout and introduce a layout-guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Xiaoyu Zhou , Xingjian Ran , Yajiao Xiong , Jinlin He , Zhiwei Lin , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

Recent developments in 3D Gaussian Splatting have significantly enhanced novel view synthesis, yet generating high-quality renderings from extreme novel viewpoints or partially observed regions remains challenging. Meanwhile, diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Jiaxin Wei , Stefan Leutenegger , Simon Schaefer

We propose 3D Super Resolution (3DSR), a novel 3D Gaussian-splatting-based super-resolution framework that leverages off-the-shelf diffusion-based 2D super-resolution models. 3DSR encourages 3D consistency across views via the use of an…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Yi-Ting Chen , Ting-Hsuan Liao , Pengsheng Guo , Alexander Schwing , Jia-Bin Huang

We introduce PointGauss, a novel point cloud-guided framework for real-time multi-object segmentation in Gaussian Splatting representations. Unlike existing methods that suffer from prolonged initialization and limited multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Wentao Sun , Hanqing Xu , Quanyun Wu , Dedong Zhang , Yiping Chen , Lingfei Ma , John S. Zelek , Jonathan Li

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Single-image 3D scene reconstruction presents significant challenges due to its inherently ill-posed nature and limited input constraints. Recent advances have explored two promising directions: multiview generative models that train on 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Junlin Hao , Peiheng Wang , Haoyang Wang , Xinggong Zhang , Zongming Guo

One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and…

Graphics · Computer Science 2024-05-31 Artur Kasymov , Bartosz Czekaj , Marcin Mazur , Jacek Tabor , Przemysław Spurek

Using the latent diffusion model has proven effective in developing novel 3D generation techniques. To harness the latent diffusion model, a key challenge is designing a high-fidelity and efficient representation that links the latent space…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Haitao Yang , Yuan Dong , Hanwen Jiang , Dejia Xu , Georgios Pavlakos , Qixing Huang