Zobrazeno 1 - 10
of 2 260
pro vyhledávání: '"Depth completion"'
Autor:
Wang, Shuling1 (AUTHOR) 11831041@zju.edu.cn, Jiang, Fengze1 (AUTHOR), Gong, Xiaojin1 (AUTHOR) gongxj@zju.edu.cn
Publikováno v:
Sensors (14248220). Oct2024, Vol. 24 Issue 19, p6270. 21p.
Depth completion using lightweight time-of-flight (ToF) depth sensors is attractive due to their low cost. However, lightweight ToF sensors usually have a limited field of view (FOV) compared with cameras. Thus, only pixels in the zone area of the im
Externí odkaz:
http://arxiv.org/abs/2411.04480
Depth completion, inferring dense depth maps from sparse measurements, is crucial for robust 3D perception. Although deep learning based methods have made tremendous progress in this problem, these models cannot generalize well across different scene
Externí odkaz:
http://arxiv.org/abs/2410.18408
Autor:
Gangopadhyay, Suchisrit, Chen, Xien, Chu, Michael, Rim, Patrick, Park, Hyoungseob, Wong, Alex
We propose UnCLe, a standardized benchmark for Unsupervised Continual Learning of a multimodal depth estimation task: Depth completion aims to infer a dense depth map from a pair of synchronized RGB image and sparse depth map. We benchmark depth comp
Externí odkaz:
http://arxiv.org/abs/2410.18074
Depth completion (DC) aims to predict a dense depth map from an RGB image and sparse depth observations. Existing methods for DC generalize poorly on new datasets or unseen sparse depth patterns, limiting their practical applications. We propose OMNI
Externí odkaz:
http://arxiv.org/abs/2411.19278
Autor:
Gregorek, Jakub, Nalpantidis, Lazaros
Even if the depth maps captured by RGB-D sensors deployed in real environments are often characterized by large areas missing valid depth measurements, the vast majority of depth completion methods still assumes depth values covering all areas of the
Externí odkaz:
http://arxiv.org/abs/2409.10202
Depth completion aims to predict dense depth maps with sparse depth measurements from a depth sensor. Currently, Convolutional Neural Network (CNN) based models are the most popular methods applied to depth completion tasks. However, despite the exce
Externí odkaz:
http://arxiv.org/abs/2409.08159
Due to the visual properties of reflection and refraction, RGB-D cameras cannot accurately capture the depth of transparent objects, leading to incomplete depth maps. To fill in the missing points, recent studies tend to explore new visual features a
Externí odkaz:
http://arxiv.org/abs/2408.00337
Autor:
Pan, Jiasheng1 (AUTHOR) pjs199999@shu.edu.cn, Zhong, Songyi2,3 (AUTHOR) yankun_yin@shu.edu.cn, Yue, Tao2 (AUTHOR), Yin, Yankun3 (AUTHOR) yanhao@shu.edu.cn, Tang, Yanhao3 (AUTHOR)
Publikováno v:
Sensors (14248220). Apr2024, Vol. 24 Issue 7, p2374. 16p.
Given the lidar measurements from an autonomous vehicle, we can project the points and generate a sparse depth image. Depth completion aims at increasing the resolution of such a depth image by infilling and interpolating the sparse depth values. Lik
Externí odkaz:
http://arxiv.org/abs/2406.11315