3 NLLLoss(最大似然损失函数) 4 MSELoss(平方损失函数) 5 DiceLoss(用于计算两个样本点的相似度的距,主要应用,语义分割等) 6 Focal Loss 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 ...
By analyzing the mesh deformation process, we pinpoint that the inappropriate usage of Chamfer Distance (CD) loss is a root cause of VC and IT problems in deep learning model. In this article, we initially demonstrate these two problems induced by CD loss with visual examples and quantitative...
一、问题描述 定义 字符串编辑距离(Edit Distance),是俄罗斯科学家 Vladimir Levenshtein 在 1965 年提出的概念,又称 Levenshtein 距离,是指两个字符串之间,由一个转变成另一个所需的最少编辑操作次数。许可的编辑操作包括: 将一个字符替换成另一个字符 插入一个字符 删除一个字符 应用 1. DNA分析: 基因学的一...
将其用于点云数据生成。全网第一次用RL控制GAN。通过数据驱动的方法填补三维数据中的数据缺失。 所采用的方法? 预训练阶段,训练一个自编码器,用于生成隐空间...;输入点云数据 PinP_{in}Pin和生成器和解码器输出数据 E−1(G(z))E^{-1}(G(z))E−1(G(z))做loss: LCH=dCH(Pin,E ...
Here is 1 public repository matching this topic... Implementation of the Chamfer Distance as a module for pyTorch modulepytorchchamfer-distancechamfer-loss UpdatedSep 5, 2023 C++ Improve this page Add a description, image, and links to thechamfer-losstopic page so that developers can more easily...
importtorchfromchamfer_distanceimportChamferDistanceaschamfer_distimporttimep1=torch.rand([10,25,3])p2=torch.rand([10,15,3])s=time.time()chd=chamfer_dist()dist1,dist2,idx1,idx2=chd(p1,p2)loss=(torch.mean(dist1))+(torch.mean(dist2))torch.cuda.synchronize()print(f"Time:{time.time(...
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 ...
Chamfer distance (CD) is a standard metric to measure the shape dissimilarity between point clouds in point cloud completion, as well as a loss function fo... F Lin,Y Yue,S Hou,... - IEEE/CVF International Conference on Computer Vision 被引量: 0发表: 0年 Learnable Chamfer Distance for...
Maintaining Natural Image Statistics with the Contextual Loss摘 要:1 介绍2 训练CNN以匹配图像分布2.1 设置2.2 KL-分歧的回顾2.3 用上下文损失来逼近KL-divergenceContextual loss:Chamfer DistanceContextual Loss与Chamfer Distance3 实证分析近似 blender曲线阵列插件 mac版本 最小化 数据集 解决方案 转载 技术领航...
we propose a simple but effective reconstruction loss, named Learnable Chamfer Distance (LCD) by dynamically paying attention to matching distances with different weight distributions controlled with a group of learnable networks. By training with adversarial strategy, LCD learns to search defects in reco...