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Related papers: DreamGaussian4D: Generative 4D Gaussian Splatting

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Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. However, 3DGS heavily depends on the initialized point cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Kai Cheng , Xiaoxiao Long , Kaizhi Yang , Yao Yao , Wei Yin , Yuexin Ma , Wenping Wang , Xuejin Chen

The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large-scale 3DGS and rendering it in real-time across various…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yang Liu , He Guan , Chuanchen Luo , Lue Fan , Naiyan Wang , Junran Peng , Zhaoxiang Zhang

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

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

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

Recent advances in 4D Gaussian Splatting (4DGS) editing still face challenges with view, temporal, and non-editing region consistency, as well as with handling complex text instructions. To address these issues, we propose 4DGS-Craft, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Lei Liu , Can Wang , Zhenghao Chen , Dong Xu

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

Recent advances in Gaussian Splatting (GS) have demonstrated its effectiveness in photo-realistic rendering and 3D reconstruction. Among these, 2D Gaussian Splatting (2DGS) is particularly suitable for surface reconstruction due to its…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Qilin Zhang , Olaf Wysocki , Boris Jutzi

Existing 4D Gaussian Splatting (4DGS) methods struggle to accurately reconstruct dynamic scenes, often failing to resolve ambiguous pixel correspondences and inadequate densification in dynamic regions. We address these issues by…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Taeho Kang , Jaeyeon Park , Kyungjin Lee , Youngki Lee

Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou

Four-dimensional computed tomography (4D CT) reconstruction is crucial for capturing dynamic anatomical changes but faces inherent limitations from conventional phase-binning workflows. Current methods discretize temporal resolution into…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Weihao Yu , Yuanhao Cai , Ruyi Zha , Zhiwen Fan , Chenxin Li , Yixuan Yuan

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

We introduce GaussianZoom, a generative zoom-in 3D reconstruction system with an iterative progressive framework that combines geometry-consistent scene modeling and multi-scale semantic reasoning to enable high-fidelity extreme zoom-in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiale Shi , Jiarui Hu , Zesong Yang , Kaixuan Luan , Hujun Bao , Zhaopeng Cui

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Florian Hahlbohm , Linus Franke , Martin Eisemann , Marcus Magnor

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but predominantly targets soft, deformable materials, leaving…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Bei Huang , Yixin Chen , Ruijie Lu , Gang Zeng , Hongbin Zha , Yuru Pei , Siyuan Huang

The field of Novel View Synthesis has been revolutionized by 3D Gaussian Splatting (3DGS), which enables high-quality scene reconstruction that can be rendered in real-time. 3DGS-based techniques typically suffer from high GPU memory and…

Graphics · Computer Science 2025-10-27 Umar Farooq , Jean-Yves Guillemaut , Adrian Hilton , Marco Volino

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng