一、简介本篇论文是MIT发表的一篇通过稀疏深度图和单张RGB图片来估计单目稠密深度图的论文。本文提出了一种单个深度回归网络可以直接从RGB-D图片中进行学习并探究了深度样本的数量对估计精度的影响。实验表明,同…
3.4 Loss Function 损失函数由propoals生成损失L_{prop}和box预测损失L_{box}组成,总的损失函数为他们的和。 propoals生成损失L_{prop}组成如下: 4.实验 5.总结 作者: 提出了一种新的两阶段三维目标检测框架,该框架结合了基于体素的检测方法和基于点的检测方法的优点。在第一阶段作者引入了基于点的球形anchor生...
# 需要导入模块: import tensorflow [as 别名]# 或者: from tensorflow importsparse_to_dense[as 别名]defkSparse(self, x, topk):print'run regular k-sparse'dim = int(x.get_shape()[1])iftopk > dim: warnings.warn('Warning: topk should not be larger than dim: %s, found: %s, using %s'...
将SparseTensor 转换为密集张量。 用法 tf.sparse.to_dense( sp_input, default_value=None, validate_indices=True, name=None ) 参数 sp_input 输入SparseTensor。 default_value 为sp_input 中未指定的索引设置的标量值。默认为零。 validate_indices 一个布尔值。如果 True ,则检查索引以确保它们按字典顺序...
http://bing.comSparse-To-Dense: Depth Prediction from Sparse Depth Samples and a Single Image字幕版之后会放出,敬请持续关注欢迎加入人工智能机器学习群:556910946,会有视频,资料放送, 视频播放量 368、弹幕量 0、点赞数 1、投硬币枚数 1、收藏人数 2、转发人数 0
STD:Sparse-to-Dense 3D Object Detector for Point Cloud(腾讯&香港大学),主要思想本文提出了一种新的两阶段3D目标检测框架,称之为稀疏到稠密三维目标检测框架(STD)。第一个阶段是自下而上的proposal生成网络,该网络使用原始点云作为输入,通过为每个点播种新的球形a
Specifically, the defective point cloud is completed and optimized in a sparse-to-dense manner of two-stages. In the first stage, we generate a sparse but complete point cloud based on a bistratal PointNet, and in the second stage, we yield a dense and high-fidelity point cloud by ...
We present a new two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD). The first stage is a bottom-up proposal generation network that uses raw point cloud as input to generate accurate proposals by seeding each point with a new spherical anchor. It achieve...
结合少量的距离信息和彩色信息进行距离图像预测 ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation) - Ewenwan/sparse-to-dense
Sparse-to-Dense: Depth Prediction fromSparse Depth Samples and a Single ImageFangchang Ma 1 and Sertac Karaman 1Abstract—We consider the problem of dense depth predictionfrom a sparse set of depth measurements and a single RGBimage. Since depth estimation from monocular images alone isinherently ...