Zobrazeno 1 - 10
of 18 871
pro vyhledávání: '"Urban scenes"'
Autor:
Mi, Zhenxing, Xu, Dan
In NeRF, a critical problem is to effectively estimate the occupancy to guide empty-space skipping and point sampling. Grid-based methods work well for small-scale scenes. However, on large-scale scenes, they are limited by predefined bounding boxes,
Externí odkaz:
http://arxiv.org/abs/2411.11374
Autor:
Liu Na'ou
More than eighty years after his death, Liu Na'ou (1905—1940) remains a fascinating figure. Liu was born in Taiwan, but early on he wrote that his future lay in Shanghai and did indeed spend the entirety of his glittering but all-too-brief career i
Neural rendering-based urban scene reconstruction methods commonly rely on images collected from driving vehicles with cameras facing and moving forward. Although these methods can successfully synthesize from views similar to training camera traject
Externí odkaz:
http://arxiv.org/abs/2407.02945
Point clouds are vital in computer vision tasks such as 3D reconstruction, autonomous driving, and robotics. However, TLS-acquired point clouds often contain virtual points from reflective surfaces, causing disruptions. This study presents a reflecti
Externí odkaz:
http://arxiv.org/abs/2407.02830
Creating large-scale virtual urban scenes with variant styles is inherently challenging. To facilitate prototypes of virtual production and bypass the need for complex materials and lighting setups, we introduce the first vision-and-text-driven textu
Externí odkaz:
http://arxiv.org/abs/2404.10681
Autor:
Wu, Ke, Zhang, Kaizhao, Zhang, Zhiwei, Yuan, Shanshuai, Tie, Muer, Wei, Julong, Xu, Zijun, Zhao, Jieru, Gan, Zhongxue, Ding, Wenchao
Online dense mapping of urban scenes forms a fundamental cornerstone for scene understanding and navigation of autonomous vehicles. Recent advancements in mapping methods are mainly based on NeRF, whose rendering speed is too slow to meet online requ
Externí odkaz:
http://arxiv.org/abs/2403.20159
The rapid growth of 3D Gaussian Splatting (3DGS) has revolutionized neural rendering, enabling real-time production of high-quality renderings. However, the previous 3DGS-based methods have limitations in urban scenes due to reliance on initial Struc
Externí odkaz:
http://arxiv.org/abs/2403.20032
The task of separating dynamic objects from static environments using NeRFs has been widely studied in recent years. However, capturing large-scale scenes still poses a challenge due to their complex geometric structures and unconstrained dynamics. W
Externí odkaz:
http://arxiv.org/abs/2403.09419
Publikováno v:
Remote Sensing. Aug2024, Vol. 16 Issue 16, p3065. 20p.
Recent advancements in the study of Neural Radiance Fields (NeRF) for dynamic scenes often involve explicit modeling of scene dynamics. However, this approach faces challenges in modeling scene dynamics in urban environments, where moving objects of
Externí odkaz:
http://arxiv.org/abs/2403.16141