English
Related papers

Related papers: Frequency-Aware Density Control via Reparameteriza…

200 papers

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu 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

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

Novel view synthesis has advanced significantly with the development of neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS). However, achieving high quality without compromising real-time rendering remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

3D Gaussian Splatting (3DGS) struggles in few-shot scenarios, where its standard adaptive density control (ADC) can lead to overfitting and bloated reconstructions. While state-of-the-art methods like FSGS improve quality, they often do so…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Abdelrhman Elrawy , Emad A. Mohammed

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

The recent advent of 3D Gaussian Splatting (3DGS) has revolutionized the 3D scene reconstruction space enabling high-fidelity novel view synthesis in real-time. However, with the exception of RawNeRF, all prior 3DGS and NeRF-based methods…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Shreyas Singh , Aryan Garg , Kaushik Mitra

High Dynamic Range (HDR) 3D reconstruction is pivotal for professional content creation in filmmaking and virtual production. Existing methods typically rely on multi-exposure Low Dynamic Range (LDR) supervision to constrain the learning…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Kaixuan Zhang , Minxian Li , Mingwu Ren , Jiankang Deng , Xiatian Zhu

Sparse-view 3D Gaussian Splatting (3DGS) presents significant challenges in reconstructing high-quality novel views, as it often overfits to the widely-varying high-frequency (HF) details of the sparse training views. While frequency…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Hung Nguyen , Runfa Li , An Le , Truong Nguyen

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 YuanZheng Wu , Jin Liu , Shunping Ji

In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly focus on exploring strong geometry regularization. Instead,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Lue Fan , Yuxue Yang , Minxing Li , Hongsheng Li , Zhaoxiang Zhang

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction. To this end, we first propose a Gaussian densification strategy based on the rendering…

Robotics · Computer Science 2024-10-03 Shuo Sun , Malcolm Mielle , Achim J. Lilienthal , Martin Magnusson

Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic images. Therefore, security concerns arise regarding the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Davide Di Nucci , Riccardo Catalini , Guido Borghi , Roberto Vezzani

We propose a novel 3D deepfake generation framework based on 3D Gaussian Splatting that enables realistic, identity-preserving face swapping and reenactment in a fully controllable 3D space. Compared to conventional 2D deepfake approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Wending Liu , Siyun Liang , Huy H. Nguyen , Isao Echizen

Recent advances in 3D Gaussian Splatting (3DGS) deliver high-quality rendering, yet the Gaussian representation exposes a new attack surface, the resource-targeting attack. This attack poisons training images, excessively inducing Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Yang Chen , Yi Yu , Jiaming He , Yueqi Duan , Zheng Zhu , Yap-Peng Tan

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable capabilities in real-time and photorealistic novel view synthesis. However, traditional 3DGS representations often struggle with large-scale scene management and…

Graphics · Computer Science 2025-08-08 Zijian Wang , Beizhen Zhao , Hao Wang

3D Gaussian Splatting (3DGS) enables photorealistic rendering but suffers from artefacts due to sparse Structure-from-Motion (SfM) initialisation. To address this limitation, we propose GP-GS, a Gaussian Process (GP) based densification…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhihao Guo , Jingxuan Su , Chenghao Qian , Shenglin Wang , Jinlong Fan , Jing Zhang , Wei Zhou , Hadi Amirpour , Yunlong Zhao , Liangxiu Han , Peng Wang
‹ Prev 1 3 4 5 6 7 10 Next ›