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Recently, 3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction, manifesting efficient and high-fidelity novel view synthesis. However, accurately representing surfaces, especially in large and complex scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yang Liu , Chuanchen Luo , Zhongkai Mao , Junran Peng , Zhaoxiang Zhang

Underwater 3D scene reconstruction faces severe challenges from light absorption, scattering, and turbidity, which degrade geometry and color fidelity in traditional methods like Neural Radiance Fields (NeRF). While NeRF extensions such as…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Wenpeng Xing , Jie Chen , Zaifeng Yang , Changting Lin , Jianfeng Dong , Chaochao Chen , Xun Zhou , Meng Han

3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. In recent times, some work has emerged that aims to extend…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Shijie Zhou , Haoran Chang , Sicheng Jiang , Zhiwen Fan , Zehao Zhu , Dejia Xu , Pradyumna Chari , Suya You , Zhangyang Wang , Achuta Kadambi

3D Gaussian Splatting is renowned for its high-fidelity reconstructions and real-time novel view synthesis, yet its lack of semantic understanding limits object-level perception. In this work, we propose ObjectGS, an object-aware framework…

Graphics · Computer Science 2025-07-22 Ruijie Zhu , Mulin Yu , Linning Xu , Lihan Jiang , Yixuan Li , Tianzhu Zhang , Jiangmiao Pang , Bo Dai

3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Stéphane Pateux , Matthieu Gendrin , Luce Morin , Théo Ladune , Xiaoran Jiang

In the fields of photogrammetry, computer vision and computer graphics, the task of neural 3D scene reconstruction has led to the exploration of various techniques. Among these, 3D Gaussian Splatting stands out for its explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-05-06 Miriam Jäger , Theodor Kapler , Michael Feßenbecker , Felix Birkelbach , Markus Hillemann , Boris Jutzi

In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radiance Field (NeRF), enabling high-fidelity photorealistic rendering in real time. Beyond…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Shuting He , Peilin Ji , Yitong Yang , Changshuo Wang , Jiayi Ji , Yinglin Wang , Henghui Ding

We present a Gaussian Splatting method for surface reconstruction using sparse input views. Previous methods relying on dense views struggle with extremely sparse Structure-from-Motion points for initialization. While learning-based…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Jiang Wu , Rui Li , Yu Zhu , Rong Guo , Jinqiu Sun , Yanning Zhang

This paper addresses the limitations of existing 3D Gaussian Splatting (3DGS) methods, particularly their reliance on adaptive density control, which can lead to floating artifacts and inefficient resource usage. We propose a novel densify…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Phurtivilai Patt , Leyang Huang , Yinqiang Zhang , Yang Lei

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differentiable 3D Gaussians. However, its rendering speed and model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Alex Hanson , Allen Tu , Geng Lin , Vasu Singla , Matthias Zwicker , Tom Goldstein

We present DGGS, a novel framework that addresses the previously unexplored challenge: $\textbf{Distractor-free Generalizable 3D Gaussian Splatting}$ (3DGS). It mitigates 3D inconsistency and training instability caused by distractor data…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Yanqi Bao , Jing Liao , Jing Huo , Yang Gao

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to efficiently and stably achieve high-quality geometric fidelity remains a core challenge. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kehua Chen , Tianlu Mao , Xinzhu Ma , Hao Jiang , Zehao Li , Zihan Liu , Shuqin Gao , Honglong Zhao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Jiaxin Guo , Jiangliu Wang , Di Kang , Wenzhen Dong , Wenting Wang , Yun-hui Liu

3D Gaussian Splatting (3DGS) has recently emerged as a powerful paradigm for photorealistic view synthesis, representing scenes with spatially distributed Gaussian primitives. While highly effective for rendering, achieving accurate and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Wenzhi Guo , Bing Wang

Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accurately in 3DGS remains challenging due to the discrete nature of Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Yi He , Tao Wang , Yi Jin , Congyan Lang , Yidong Li , Haibin Ling

Underwater scene reconstruction is a critical tech-nology for underwater operations, enabling the generation of 3D models from images captured by underwater platforms. However, the quality of underwater images is often degraded due to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Junhao Shi , Jisheng Xu , Jianping He , Zhiliang Lin

The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Huapeng Li , Wenxuan Song , Tianao Xu , Alexandre Elsig , Jonas Kulhanek

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu
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