FP层的作用是将SA层抽象后的点特征再映射回原始的点云，可以理解为上图中Point-RCNN的Point Cloud De...
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SEED: A Simple and Effective 3D DETR in Point Clouds [det] DSPDet3D: Dynamic Spatial Pruning for 3D Small Object Detection [det; PyTorch] General Geometry-aware Weakly Supervised 3D Object Detection [det; PyTorch] SegPoint: Segment Any Point Cloud via Large Language Model [seg] Open-Vocabular...
According to the provided point cloud, a 3D model was made and a floor plan was also drawn up.
一个通用的 3D/2.5D 人脸分析框架如上图所示。我们通过设备获取人脸的 3D/2.5D 表示(Mesh、Point Cloud、Depth),经过一些预处理操作如球形剪裁,噪点去除,深度缺失修复,点云配准等进一步获取可用的 3D/2.5D 人脸。 接下来对预处理后的人脸进行表征,表征的方式有很多,比如采用表面法向,曲率,UV-Map 或常用的 CNN...
对于几何建模,我们应用 PDS,从 ShapeNetCoreV2 数据集和 ModelNet40 数据集中统一采样 2048 个空间点。对于视觉建模,我们采用了与第 4.2 节中描述相同的viewpoint配置,进而在ShapeNetCoreV2 数据集上生成多视图的图像渲染。 Teacher 分支的架构。如图 5所示。我们构建了一个标准卷积的 auto-encoder,用于无监督图像的...
3D-SSD[12]通过对之前Point-based方法的各个模块进行分析,得出结论:FP(Feature Propagation)层和细化层(Refinement)是系统运行速度的瓶颈。 FP层的作用是将SA层抽象后的点特征再映射回原始的点云,可以理解为上图中Point-RCNN的Point Cloud Decoder。这一步非常必要,因为SA输出的抽象点并不能很好的覆盖所有的物体,...
Lan, Shiyi, et al. "Modeling local geometric structure of 3D point clouds using Geo-CNN."Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019. [paper] Rao, Yongming, Jiwen Lu, and Jie Zhou. "Spherical fractal convolutional neural networks for point cloud recogniti...
PointConv是3D连续卷积算子的一种蒙特卡罗近似扩展。对于每个卷积滤波器,它使用MLP来近似加权函数,然后应用密度标度(density scale)函数来重新估计权重函数的参数。Sec. 3.1介绍了PointConv层的结构。Sec. 3.2引入PointDeconv,使用PointConv层反卷积点云特征。 3.1. 3D 点云上的卷积...
The combined approaches yield a simplified solid room-wise polygonal 3D model containing segmented and labelled point clouds. The pipeline has been evaluated on scans of 2 to 3-story office buildings. The results demonstrate that the pipeline can segment and label scans with high accuracy, and ...