12.SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again - Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, Nassir Navab. [Paper:https://arxiv.org/pdf/1711.10006.pdf] 13.Deep Learning of Local RGB-...
Aside from these RGB-D-based methods, a few RGB-based methods have been proposed. Manhardt et al. [25] estimate pose and a point set from monocular images. While their method only uses RGB information during inference, they show that unannotated depth data can be used to close the synthet...
[23] Li J, Liu Y, Gong D, Shi QF, Yuan X, Zhao CX, Reid I. RGBD based dimensional decomposition residual network for 3D semantic scene completion. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019: 7685-7694. [24] Chen Y, Garbade M, Gall J. 3D sem...
Finally, we discuss several challenges and open directions of RGB-D based salient object detection for future research. 3. 目标框架 3.1 显著性目标检测发展历史 2012-2016是显著性目标检测的传统方法,2017年以后开始出现了基于深度学习的模型。 3.2 RGB图像与深度图相关计算所采取的不同的融合策略 主要是早期...
例如,通过图8下两幅图中的网格的TSDF数值分布,我们可以很快还原出模型表面的形状和位置。这种方法通常被称为基于体数据的方法(Volumetric-based method)。该方法的核心思想是,通过不断更新并“融合”(fusion)TSDF这种类型的测量值,我们能够 越来越接近所需要的真实值。
[186]基于此提出了RGB-D SLAM问题的改进和优化。系统前端从每个帧的RGB图像中提取特征,结合RANSAC和ICP算法以获得并使用EMM(环境测量模型)模型来验证运动估计,后端基于姿势图优化构建地图。 5参考 [1] Vision-Based Environmental Perception for ...
Recognition of space objects including spacecraft and debris is one of the main components in the space situational awareness (SSA) system. Various tasks such as satellite formation, on-orbit servicing, and active debris removal require object recognitio
论文标题:NID-SLAM: NEURAL IMPLICIT REPRESENTATION-BASED RGB-D SLAM IN DYNAMIC ENVIRONMENTS 论文链接:https://arxiv.org/abs/2401.01189 1. 原文摘要 神经隐式表示已经被探索用于增强视觉SLAM掩码算法,特别是在提供高保真的密集地图方面。现有的方法在静态场景中表现出强大的鲁棒性,但却难以应对移动物体造成的干扰...
首先采用DBSCAN(density-based spatial clustering of applications with noise)算法将具有相同标记的点云分割成不同聚类[14];然后将三维语义地图中的语义标签匹配至LiDAR点云分割簇中。三维语义地图中的点云与LiDAR点云分割簇之间的关系如图 4所示。 图4三...