PDF:Review: deep learning on 3D point clouds Abstract Point cloud is point sets defined in 3D metric space. Point cloud has become one of the most significant data format for 3D representation. Its gaining increased popularity as a result of increased availability of acquisition devices, such as...
出发点:设计能处理3D几何数据(例如point clouds或meshes)的深度学习架构;point clouds是简单统一的结构,避免了meshes组合不规则性和复杂性,因此更容易学习; point cloud是一组点,需要排列不变性(进行某些对对称化)和刚体运动不变性; PointNet简述:PointNet是一种直接处理point cloud的新型神经网络,直接将无序point cloud...
multi-view data, 3D projections, RGB-D data, and volumetric data (voxel and octree). The second category is the non-Euclidean representations, where no global parameterization lacks the gridded array structure, such as point clouds, graphs, and polygon meshes. The authors also detailed the DL...
While deep learning techniques are mainly applied to data with a structured grid, point cloud, on the other hand, is unstructured. The unstructuredness of point clouds makes use of deep learning for its processing directly very challenging. Earlier approaches overcome this challenge by preprocessing ...
Deep learning (DL) has been established as a powerful tool for data processing, reporting remarkable performance enhancements compared to traditional methods for all basic 2D vision tasks. However new challenges are emerging when it comes to processing unstructured 3D point clouds. This work aims to...
Deep learning based computer vision under the prism of 3D point clouds: a systematic review Point clouds consist of 3D data points and are among the most considerable data formats for 3D representations. Their popularity is due to their broad appl... KA Tychola,E Vrochidou,GA Papakostas - ...
We therefore classified the current deep learning-based animal detection studies into five categories: image level, point level, bounding box level, instance segmentation level, and specific information level based on the image annotation method and the degree of richness of the animal information ...
Chen Q, Tang S, Yang Q, Fu S (2019d) Cooper: cooperative perception for connected autonomous vehicles based on 3d point clouds. In: 2019 IEEE 39th International Conference on distributed computing systems (ICDCS), pp 514–524. IEEE
Simon M, Milz S, Amende K, Gross H-M (2018) Complex-YOLO: an euler-region-proposal for real-time 3d object detection on point clouds. In: European Conference on Computer Vision Workshops Simon M, Rodner E, Denzler J (2016) Imagenet pre-trained models with batch normalization. arXiv:16...
Review: deep learning on 3D point clouds Point cloud is point sets defined in 3D metric space. Point cloud has become one of the most significant data format for 3D representation. Its gaining increased popularity as a result of increased availability of acquisition devices, such as LiDAR, as ...