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Related papers: Object-Centric 2D Gaussian Splatting: Background R…

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3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Shen Chen , Jiale Zhou , Lei Li

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

Recent advances in real-time neural rendering using point-based techniques have enabled broader adoption of 3D representations. However, foundational approaches like 3D Gaussian Splatting impose substantial storage overhead, as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhiwen Fan , Kevin Wang , Kairun Wen , Zehao Zhu , Dejia Xu , Zhangyang Wang

Recently, 3D Gaussian Splatting (3DGS) has become one of the mainstream methodologies for novel view synthesis (NVS) due to its high quality and fast rendering speed. However, as a point-based scene representation, 3DGS potentially…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhaoliang Zhang , Tianchen Song , Yongjae Lee , Li Yang , Cheng Peng , Rama Chellappa , Deliang Fan

We introduce Contrastive Gaussian Clustering, a novel approach capable of provide segmentation masks from any viewpoint and of enabling 3D segmentation of the scene. Recent works in novel-view synthesis have shown how to model the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Myrna C. Silva , Mahtab Dahaghin , Matteo Toso , Alessio Del Bue

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

Gaussian Splatting has emerged as a leading method for novel view synthesis, offering superior training efficiency and real-time inference compared to NeRF approaches, while still delivering high-quality reconstructions. Beyond view…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Lorenzo Rutayisire , Nicola Capodieci , Fabio Pellacini

Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructions, they either rely on costly human annotations for object…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Carl Lindström , Mahan Rafidashti , Maryam Fatemi , Lars Hammarstrand , Martin R. Oswald , Lennart Svensson

We present SplatFace, a novel Gaussian splatting framework designed for 3D human face reconstruction without reliance on accurate pre-determined geometry. Our method is designed to simultaneously deliver both high-quality novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jiahao Luo , Jing Liu , James Davis

Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiaqi Lin , Zhihao Li , Xiao Tang , Jianzhuang Liu , Shiyong Liu , Jiayue Liu , Yangdi Lu , Xiaofei Wu , Songcen Xu , Youliang Yan , Wenming Yang

Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangsen Chen , Hao Wang

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

In cluttered scenes with inevitable occlusions and incomplete observations, selecting informative viewpoints is essential for building a reliable representation. In this context, 3D Gaussian Splatting (3DGS) offers a distinct advantage, as…

Robotics · Computer Science 2026-02-10 Seunghoon Jeong , Eunho Lee , Jeongyun Kim , Ayoung Kim

Planes are fundamental primitives of 3D sences, especially in man-made environments such as indoor spaces and urban streets. Representing these planes in a structured and parameterized format facilitates scene editing and physical…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Ruitong Gan , Junran Peng , Yang Liu , Chuanchen Luo , Qing Li , Zhaoxiang Zhang

Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation. However, the substantial data volume of Gaussian splatting impedes its practical utility in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Xiangrui Liu , Xinju Wu , Pingping Zhang , Shiqi Wang , Zhu Li , Sam Kwong

Seamless integration of both aerial and street view images remains a significant challenge in neural scene reconstruction and rendering. Existing methods predominantly focus on single domain, limiting their applications in immersive…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Lihan Jiang , Kerui Ren , Mulin Yu , Linning Xu , Junting Dong , Tao Lu , Feng Zhao , Dahua Lin , Bo Dai

Implicit neural representation methods have shown impressive advancements in learning 3D scenes from unstructured in-the-wild photo collections but are still limited by the large computational cost of volumetric rendering. More recently, 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Hiba Dahmani , Moussab Bennehar , Nathan Piasco , Luis Roldao , Dzmitry Tsishkou

Gaussian splatting (GS) for 3D reconstruction has become quite popular due to their fast training, inference speeds and high quality reconstruction. However, GS-based reconstructions generally consist of millions of Gaussians, which makes…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Anil Armagan , Albert Saà-Garriga , Bruno Manganelli , Mateusz Nowak , Mehmet Kerim Yucel

We present TranSplat, a method for instant, accurate object relighting within the Gaussian Splatting (GS) framework. Rather than relying on costly inverse rendering routines, we propose a BRDF-free radiance transfer strategy that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Boyang Tony Yu , Yanlin Jin , Yun He , Akshat Dave , Ravi Ramamoorthi , Guha Balakrishnan

Underwater 3D reconstruction and appearance restoration are hindered by the complex optical properties of water, such as wavelength-dependent attenuation and scattering. Existing Neural Radiance Fields (NeRF)-based methods struggle with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Xinrui Zhang , Yufeng Wang , Shuangkang Fang , Zesheng Wang , Dacheng Qi , Wenrui Ding
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