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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

3D Gaussian Splatting (3DGS) has made remarkable progress in RGBD SLAM. Current methods usually use 3D Gaussians or view-tied 3D Gaussians to represent radiance fields in tracking and mapping. However, these Gaussians are either too…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Pengchong Hu , Zhizhong Han

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

Reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface reconstruction and novel view synthesis. Existing Gaussian splatting methods either fail to model…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Ningjing Fan , Yiqun Wang , Dongming Yan , Peter Wonka

High-fidelity reconstruction of deformable tissues from endoscopic videos remains challenging due to the limitations of existing methods in capturing subtle color variations and modeling global deformations. While 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Qun Ji , Peng Li , Mingqiang Wei

We introduce Crowd-Sourced Splatting (CSS), a novel 3D Gaussian Splatting (3DGS) pipeline designed to overcome the challenges of pose-free scene reconstruction using crowd-sourced imagery. The dream of reconstructing historically…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Runze Chen , Mingyu Xiao , Haiyong Luo , Fang Zhao , Fan Wu , Hao Xiong , Qi Liu , Meng Song

Transmissive scenes are ubiquitous in daily life, yet reconstructing and rendering them remains highly challenging due to the inherent entanglement between near-field reflections from the surrounding environment on the transmissive surface,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhenyu Liang , Xiao Zhang , Tianchao Li , Jack C. P. Cheng , Chi-Keung Tang

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 (3D GS) achieves impressive results in novel view synthesis for small, single-object scenes through Gaussian ellipsoid initialization and adaptive density control. However, when applied to large-scale remote sensing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 BoCheng Li , WenJuan Zhang , Bing Zhang , YiLing Yao , YaNing Wang

3D Gaussian splatting (3D-GS) is a new rendering approach that outperforms the neural radiance field (NeRF) in terms of both speed and image quality. 3D-GS represents 3D scenes by utilizing millions of 3D Gaussians and projects these…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Joongho Jo , Hyeongwon Kim , Jongsun Park

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xiaoyang Lyu , Yang-Tian Sun , Yi-Hua Huang , Xiuzhe Wu , Ziyi Yang , Yilun Chen , Jiangmiao Pang , Xiaojuan Qi

Open-vocabulary 3D scene understanding is crucial for applications requiring natural language-driven spatial interpretation, such as robotics and augmented reality. While 3D Gaussian Splatting (3DGS) offers a powerful representation for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Wei Sun , Yanzhao Zhou , Jianbin Jiao , Yuan Li

This paper presents Planar Gaussian Splatting (PGS), a novel neural rendering approach to learn the 3D geometry and parse the 3D planes of a scene, directly from multiple RGB images. The PGS leverages Gaussian primitives to model the scene…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Farhad G. Zanjani , Hong Cai , Hanno Ackermann , Leila Mirvakhabova , Fatih Porikli

Efficient and accurate object pose estimation is an essential component for modern vision systems in many applications such as Augmented Reality, autonomous driving, and robotics. While research in model-based 6D object pose estimation has…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Yufeng Jin , Vignesh Prasad , Snehal Jauhri , Mathias Franzius , Georgia Chalvatzaki

Reconstructing translucent objects from multi-view images is a difficult problem. Previously, researchers have used differentiable path tracing and the neural implicit field, which require relatively large computational costs. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Youwen Yuan , Xi Zhao

High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state-of-the-art novel view synthesis results with high rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Matias Turkulainen , Xuqian Ren , Iaroslav Melekhov , Otto Seiskari , Esa Rahtu , Juho Kannala

We propose two novel ideas (adoption of deferred rendering and mesh-based representation) to improve the quality of 3D Gaussian splatting (3DGS) based inverse rendering. We first report a problem incurred by hidden Gaussians, where…

Graphics · Computer Science 2024-09-17 Euntae Choi , Sungjoo Yoo

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

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

Efficiently synthesizing novel views from sparse inputs while maintaining accuracy remains a critical challenge in 3D reconstruction. While advanced techniques like radiance fields and 3D Gaussian Splatting achieve rendering quality and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Chenlu Zhan , Yufei Zhang , Yu Lin , Gaoang Wang , Hongwei Wang
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