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3D Gaussian Splatting (3DGS) has transformed novel-view synthesis with its fast, interpretable, and high-fidelity rendering. However, its resource requirements limit its usability. Especially on constrained devices, training performance…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Saswat Subhajyoti Mallick , Rahul Goel , Bernhard Kerbl , Francisco Vicente Carrasco , Markus Steinberger , Fernando De La Torre

3D Gaussian Splatting (3DGS) based Simultaneous Localization and Mapping (SLAM) systems can largely benefit from 3DGS's state-of-the-art rendering efficiency and accuracy, but have not yet been adopted in resource-constrained edge devices…

Hardware Architecture · Computer Science 2025-10-10 Leshu Li , Jiayin Qin , Jie Peng , Zishen Wan , Huaizhi Qu , Ye Han , Pingqing Zheng , Hongsen Zhang , Yu Cao , Tianlong Chen , Yang Katie Zhao

While 3D Gaussian Splatting (3DGS) has demonstrated impressive real-time rendering performance, its efficacy remains constrained by a reliance on heuristic density control. Despite numerous refinements to these handcrafted rules, such…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhenhua Ning , Xin Li , Jun Yu , Guangming Lu , Yaowei Wang , Wenjie Pei

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

Recently, 3D Gaussian Splatting (3DGS) has exceled in novel view synthesis (NVS) with its real-time rendering capabilities and superior quality. However, it faces challenges for high-resolution novel view synthesis (HRNVS) due to the coarse…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Shiyun Xie , Zhiru Wang , Xu Wang , Yinghao Zhu , Chengwei Pan , Xiwang Dong

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

Recent advancements in 3D reconstruction coupled with neural rendering techniques have greatly improved the creation of photo-realistic 3D scenes, influencing both academic research and industry applications. The technique of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Zexu Huang , Min Xu , Stuart Perry

3D Gaussian Splatting (3DGS) has emerged as promising alternative in 3D representation. However, it still suffers from high training cost. This paper introduces LiteGS, a high performance framework that systematically optimizes the 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Kaimin Liao , Hua Wang , Zhi Chen , Luchao Wang , Yaohua Tang

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

We propose R3GS, a robust reconstruction and relocalization framework tailored for unconstrained datasets. Our method uses a hybrid representation during training. Each anchor combines a global feature from a convolutional neural network…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Xu yan , Zhaohui Wang , Rong Wei , Jingbo Yu , Dong Li , Xiangde Liu

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

3D Gaussian Splatting (3DGS) combines classic image-based rendering, pointbased graphics, and modern differentiable techniques, and offers an interesting alternative to traditional physically-based rendering. 3DGS-family models are far from…

Graphics · Computer Science 2025-09-29 Weikai Lin , Sushant Kondguli , Carl Marshall , Yuhao Zhu

The dominant 3D Gaussian splatting (3DGS) acceleration methods fail to properly regulate the number of Gaussians during training, causing redundant computational time overhead. In this paper, we propose FastGS, a novel, simple, and general…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shiwei Ren , Tianci Wen , Yongchun Fang , Biao Lu

We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneous spatial and spectral renderings by encoding material…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Christopher Thirgood , Oscar Mendez , Erin Chao Ling , Jon Storey , Simon Hadfield

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

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

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

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) has made significant strides in real-time 3D scene reconstruction, but faces memory scalability issues in high-resolution scenarios. To address this, we propose Hierarchical Gaussian Splatting (HRGS), a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Changbai Li , Haodong Zhu , Hanlin Chen , Juan Zhang , Tongfei Chen , Shuo Yang , Shuwei Shao , Wenhao Dong , Baochang Zhang

3D Gaussian Splatting (3DGS) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magnitude of view-space positional gradients to grow Gaussians to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Qingshan Xu , Jiequan Cui , Xuanyu Yi , Yuxuan Wang , Yuan Zhou , Yew-Soon Ong , Hanwang Zhang
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