Results 121 to 130 of about 2,993 (218)

PlantGaussian: Exploring 3D Gaussian splatting for cross-time, cross-scene, and realistic 3D plant visualization and beyond

Crop Journal
Observing plants across time and diverse scenes is critical in uncovering plant growth patterns. Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.
Peng Shen, Xueyao Jing, Wenzhe Deng, Hanyue Jia, Tingting Wu   +4 more
doaj   +1 more source

Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data Generation

Generating synthetic images is a useful method for cheaply obtaining labeled data for training computer vision models. However, obtaining accurate 3D models of relevant objects is necessary, and the resulting images often have a gap in realism due to challenges in simulating lighting effects and camera artifacts.
Bram Vanhele, Brent Zoomers, Jeroen Put, Frank Van Reeth, Nick Michiels   +4 more
openaire   +3 more sources

RD-SLAM: Real-Time Dense SLAM Using Gaussian Splatting

Applied Sciences
Simultaneous localization and mapping (SLAM) is fundamental for intelligent mobile units to perform diverse tasks. Recent work has shown that integrating neural rendering and SLAM showed promising results in photorealistic environment reconstruction ...
Chaoyang Guo, Chunyan Gao, Yiyang Bai, Xiaoling Lv   +3 more
doaj   +1 more source

Li-GS: a fast 3D Gaussian reconstruction method assisted by LiDAR point clouds

Big Earth Data
Digital twin technology, serving as a bridge between the physical and digital worlds, has demonstrated significant potential across various fields. In the domain of 3D reconstruction, recent advancements in Neural Radiance Fields (NeRF) and 3D Gaussian ...
Wenzhuo Chen, Ruofei Zhong, Kangfei Wang, Donghai Xie   +3 more
doaj   +1 more source

BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting

Project Page and Source Code: https://lingzhezhao.github.io/BAD-Gaussians/
Lingzhe Zhao, Peng Wang, Peidong Liu
openaire   +2 more sources

Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

This paper aims to tackle the problem of modeling dynamic urban streets for autonomous driving scenes. Recent methods extend NeRF by incorporating tracked vehicle poses to animate vehicles, enabling photo-realistic view synthesis of dynamic urban street scenes. However, significant limitations are their slow training and rendering speed.
Yan, Yunzhi, Lin, Haotong, Zhou, Chenxu, Wang, Weijie, Sun, Haiyang, Zhan, Kun, Lang, Xianpeng, Zhou, Xiaowei, Peng, Sida   +8 more
openaire   +2 more sources

Poison-splat: Computation Cost Attack on 3D Gaussian Splatting

3D Gaussian splatting (3DGS), known for its groundbreaking performance and efficiency, has become a dominant 3D representation and brought progress to many 3D vision tasks. However, in this work, we reveal a significant security vulnerability that has been largely overlooked in 3DGS: the computation cost of training 3DGS could be maliciously tampered ...
Lu, Jiahao, Zhang, Yifan, Shen, Qiuhong, Wang, Xinchao, Yan, Shuicheng   +4 more
openaire   +2 more sources

A review of dynamic scene reconstruction based on neural representation

Dianxin kexue
Dynamic scene reconstruction holds significant research value in the fields of computer vision and virtual reality. Recent advancements in neural representation technologies have facilitated rapid progress in this task.
LU Ping, SUN Junjie, LI Wan, LIN Jiaxin, LIU Hong, LIU Hong, FENG Daquan   +6 more
doaj  

Depth-Semantic-gaussian-splatting

3D Gaussian Splatting (3D GS), leveraging its efficient explicit radiance field representation, demonstrates significant potential for modeling complex 3D scenes leveraging its efficient explicit radiance field representation. However, the technology still faces limitations in geospatial applicability, particularly regarding multi-level scene parsing ...
openaire   +1 more source

ReSplat: Learning Recurrent Gaussian Splats

Project page: https://haofeixu.github.io/resplat/
Xu, Haofei, Barath, Daniel, Geiger, Andreas, Pollefeys, Marc   +3 more
openaire   +2 more sources