English
Related papers

Related papers: NeRF Is a Valuable Assistant for 3D Gaussian Splat…

200 papers

Current Simultaneous Localization and Mapping (SLAM) methods based on Neural Radiance Fields (NeRF) or 3D Gaussian Splatting excel in reconstructing static 3D scenes but struggle with tracking and reconstruction in dynamic environments,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Mingrui Li , Yiming Zhou , Hongxing Zhou , Xinggang Hu , Florian Roemer , Hongyu Wang , Ahmad Osman

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differentiable 3D Gaussians. However, its rendering speed and model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Alex Hanson , Allen Tu , Geng Lin , Vasu Singla , Matthias Zwicker , Tom Goldstein

Novel view synthesis (NVS) aims to generate images at arbitrary viewpoints using multi-view images, and recent insights from neural radiance fields (NeRF) have contributed to remarkable improvements. Recently, studies on generalizable NeRF…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Youngho Yoon , Hyun-Kurl Jang , Kuk-Jin Yoon

Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from underfitting with blurred renderings on large-scale scenes due to limited model capacity. Recent approaches propose to geographically divide the scene and adopt…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Linning Xu , Yuanbo Xiangli , Sida Peng , Xingang Pan , Nanxuan Zhao , Christian Theobalt , Bo Dai , Dahua Lin

The ability for robots to perform efficient and zero-shot grasping of object parts is crucial for practical applications and is becoming prevalent with recent advances in Vision-Language Models (VLMs). To bridge the 2D-to-3D gap for…

Robotics · Computer Science 2024-09-04 Mazeyu Ji , Ri-Zhao Qiu , Xueyan Zou , Xiaolong Wang

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

Current 3D stylization techniques primarily focus on static scenes, while our world is inherently dynamic, filled with moving objects and changing environments. Existing style transfer methods primarily target appearance -- such as color…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Nhat Phuong Anh Vu , Abhishek Saroha , Or Litany , Daniel Cremers

Thermography is especially valuable for the military and other users of surveillance cameras. Some recent methods based on Neural Radiance Fields (NeRF) are proposed to reconstruct the thermal scenes in 3D from a set of thermal and RGB…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Rongfeng Lu , Hangyu Chen , Zunjie Zhu , Yuhang Qin , Ming Lu , Le Zhang , Chenggang Yan , Anke Xue

Wireless channel modeling is a key building block for next-generation wireless systems. Predicting the channel state information (CSI) across different transmitter locations can substantially reduce the pilot and feedback overhead of…

Signal Processing · Electrical Eng. & Systems 2026-05-18 Chenghong Bian , Meng Hua , Deniz Gunduz

Image blending aims to combine multiple images seamlessly. It remains challenging for existing 2D-based methods, especially when input images are misaligned due to differences in 3D camera poses and object shapes. To tackle these issues, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Hyunsu Kim , Gayoung Lee , Yunjey Choi , Jin-Hwa Kim , Jun-Yan Zhu

While novel view synthesis (NVS) for dynamic scenes has seen significant progress, reconstructing temporally consistent geometric surfaces remains a challenge. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) offer powerful…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Minje Kim , Younghyun Noh , Jaesoon Kim , Tae-Kyun Kim

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

3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

We propose NEDS-SLAM, a dense semantic SLAM system based on 3D Gaussian representation, that enables robust 3D semantic mapping, accurate camera tracking, and high-quality rendering in real-time. In the system, we propose a Spatially…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Yiming Ji , Yang Liu , Guanghu Xie , Boyu Ma , Zongwu Xie

Neural Radiance Fields (NeRF) have shown impressive novel view synthesis results; nonetheless, even thorough recordings yield imperfections in reconstructions, for instance due to poorly observed areas or minor lighting changes. Our goal is…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Barbara Roessle , Norman Müller , Lorenzo Porzi , Samuel Rota Bulò , Peter Kontschieder , Matthias Nießner

Neural Radiance Field (NeRF) has been widely recognized for its excellence in novel view synthesis and 3D scene reconstruction. However, their effectiveness is inherently tied to the assumption of static scenes, rendering them susceptible…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Jiahao Chen , Yipeng Qin , Lingjie Liu , Jiangbo Lu , Guanbin Li

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

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

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

Neural Radiance Fields (NeRF) achieves photo-realistic image rendering from novel views, and the Neural Scene Graphs (NSG) \cite{ost2021neural} extends it to dynamic scenes (video) with multiple objects. Nevertheless, computationally heavy…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Yeji Song , Chaerin Kong , Seoyoung Lee , Nojun Kwak , Joonseok Lee
‹ Prev 1 4 5 6 7 8 10 Next ›