Chamfer Distance是一种衡量两个点集之间相似度的度量方法。给定两个点集PPP和QQQ,Chamfer Distance定义为: dCD(P,Q)=1∣P∣∑p∈Pminq∈Q∥p−q∥22+1∣Q∣∑q∈Qminp∈P∥q−p∥22d_{CD}(P, Q) = \frac{1}{|P|} \sum_{p \in P} \min_{q \in Q} \|p - q\|_2^2 ...
7 Chamfer Distance(CD、倒角距离) 8 Earth Mover’s Distance (EMD、推土机距离) 9 Density-aware Chamfer Distance (DCD) 10 smooth L1 loss(faster RCNN 和 SSD 使用) 11 Iou Loss | Glou Loss|DIoU Loss|CIoU Loss 导航栏 前言 损失函数的作用是帮助神经网络的输出结果与真实标签作比较,使得神经网络和...
In this work, we propose a new method named Learnable Chamfer Distance (LCD) to evaluate the reconstruction loss by measuring the average point-to-point distance weighted with dynamically updated distributions. In this work, we use the static matching rules in CD [8] to calculate the matching ...
In this article, we initially demonstrate these two problems induced by CD loss with visual examples and quantitative analyses. Then, we propose a fine-grained reconstruction method CD2 by employing Chamfer distance twice to perform a plausible and adaptive deformation. Extensive experiments on two 3D...
Chamfer Distance (CD) and Earth Mover's Distance (EMD) are two broadly adopted metrics for measuring the similarity between two point sets. However, CD is usually insensitive to mismatched local density, and EMD is usually dominated by global distribution while overlooks the fidelity of detailed ...
距离变换的主要目的是通过识别目标点和背景点,将二值图像转换为灰度图像。 距离变换主要分为欧氏距离变换和非欧氏距离变换。 非欧距离变换包括棋盘距离变换、城市街区距离变换和倒角距离变换。 棋盘距离:| x1 - x2 | + | y1 - y2 | 城市街区距离:max( | x1 - x2 |, | y1 - y2 | ) ...
pytorch——计算两个等大无序点云中的距离Earth Mover Distance 目前要做两个无序点集之间的相似性计算,在看过Chamfer Distance后,个人觉得CD的计算方式决定了其无法处理两个点集整体分布差异大,但是局部有部分点距离很近的情况,而这种情况在点集中是一定可能出现的,因此使用EMD可以保证每个点集都有一一对应的整体...
We utilize AdaBoost to learn a Normalized Oriented Chamfer Distance (NOCD). Our experimental results demonstrate that it boosts the detection rate of the oriented chamfer distance. The simplicity and ease of training of NOCD on a small number of training samples promise that it can replace ...
We define a Normalized Oriented Chamfer Distance as N OCD(T, x) = H(T, x). While OCD is a distance in that the smaller is OCD value the better, NOCD is a similarity measure, i.e., the larger the NOCD value, the most likely the target object is present at location x. We use...
The official repository of the paper "Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance" - GitHub - Zhang-VISLab/IROS2024-LossDistillationWeightedCD: The official repository of the paper "Loss Distillation