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3D Gaussian Splatting (3DGS) has emerged as a leading framework for novel view synthesis, yet its core optimization challenges remain underexplored. We identify two key issues in 3DGS optimization: entrapment in suboptimal local optima and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Ziyang Huang , Jiagang Chen , Jin Liu , Shunping Ji

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

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

3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purpose and not tailored to the structure of the problem. In…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Naama Pearl , Stefano Esposito , Haofei Xu , Amit Peleg , Patricia Gschossmann , Lorenzo Porzi , Peter Kontschieder , Gerard Pons-Moll , Andreas Geiger

3D Gaussian Splatting (3DGS) has become one of the most influential works in the past year. Due to its efficient and high-quality novel view synthesis capabilities, it has been widely adopted in many research fields and applications.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Glenn Grubert , Florian Barthel , Anna Hilsmann , Peter Eisert

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

3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usually generate plausible outputs and face significant…

Graphics · Computer Science 2025-07-22 Beizhen Zhao , Yifan Zhou , Sicheng Yu , Zijian Wang , Hao Wang

3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has achieved high-quality reconstruction and real-time rendering of complex scenes. However, the rasterization pipeline still suffers from unnecessary overhead…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Xinzhe Wang , Ran Yi , Lizhuang Ma

3D Gaussian Splatting (3DGS) has recently advanced radiance field reconstruction by offering superior capabilities for novel view synthesis and real-time rendering speed. However, its strategy of blending optimization and adaptive density…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Rong Liu , Rui Xu , Yue Hu , Meida Chen , Andrew Feng

3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanced real-time rendering performance. However, due to the flaw…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Zongxin Ye , Wenyu Li , Sidun Liu , Peng Qiao , Yong Dou

Novel-view synthesis plays a crucial role in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent approaches, such as 3D Gaussian Splatting (3DGS), have emerged as state-of-the-art solutions, offering…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Ankit Dhiman , Tao Lu , R Srinath , Emre Arslan , Angela Xing , Yuanbo Xiangli , R Venkatesh Babu , Srinath Sridhar

3D Gaussian Splatting (3DGS) is a powerful reconstruction technique, but it needs to be initialized from accurate camera poses and high-fidelity point clouds. Typically, the initialization is taken from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jizong Peng , Tze Ho Elden Tse , Kai Xu , Wenchao Gao , Angela Yao

3D Gaussian Splatting (3DGS) has shown impressive results in real-time novel view synthesis. However, it often struggles under sparse-view settings, producing undesirable artifacts such as floaters, inaccurate geometry, and overfitting due…

Graphics · Computer Science 2025-09-23 Gurutva Patle , Nilay Girgaonkar , Nagabhushan Somraj , Rajiv Soundararajan

3D Gaussian Splatting (3DGS) has demonstrated outstanding performance in novel view synthesis, achieving a balance between rendering quality and real-time performance. 3DGS employs Adaptive Density Control (ADC) to increase the number of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Xiaobin Deng , Changyu Diao , Min Li , Ruohan Yu , Duanqing Xu

We present 3DGS-LM, a new method that accelerates the reconstruction of 3D Gaussian Splatting (3DGS) by replacing its ADAM optimizer with a tailored Levenberg-Marquardt (LM). Existing methods reduce the optimization time by decreasing the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Lukas Höllein , Aljaž Božič , Michael Zollhöfer , Matthias Nießner

The recent advances in 3D Gaussian Splatting (3DGS) show promising results on the novel view synthesis (NVS) task. With its superior rendering performance and high-fidelity rendering quality, 3DGS is excelling at its previous NeRF…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yu Chen , Gim Hee Lee

3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods often require millions of Gaussians to capture complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anh Thuan Tran , Jana Kosecka

3D Gaussian Splatting (3DGS) has emerged as a promising 3D reconstruction technique. The traditional 3DGS training pipeline follows three sequential steps: Gaussian densification, Gaussian projection, and color splatting. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junyi Wu , Jiaming Xu , Jinhao Li , Yongkang Zhou , Jiayi Pan , Xingyang Li , Guohao Dai

This paper presents an end-to-end framework for reconstructing 3D parametric curves directly from multi-view edge maps. Contrasting with existing two-stage methods that follow a sequential ``edge point cloud reconstruction and parametric…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Zhirui Gao , Renjiao Yi , Yaqiao Dai , Xuening Zhu , Wei Chen , Chenyang Zhu , Kai Xu

3D Gaussian Splatting (3DGS) has emerged as a mainstream solution for novel view synthesis and 3D reconstruction. By explicitly encoding a 3D scene using a collection of Gaussian kernels, 3DGS achieves high-quality rendering with superior…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Lei Lan , Tianjia Shao , Zixuan Lu , Yu Zhang , Chenfanfu Jiang , Yin Yang
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