2018cvpr-点云分类、分割等相关论文


Honorable Mention:


SPLATNet: Sparse Lattice Networks for Point Cloud Processing
UMass Amherst & Nvidia
将点视为自高维网格中采样出的稀疏集合的方式来处理点云数据


Spotlight:


PointGrid: A Deep Network for 3D Shape Understanding
University of Missouri – Columbia
Pointnet与网格化的结合,一个网格中可以包含多个点


SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance
Segmentation
University of Southern California
点云数据上的实例分割


Recurrent Slice Networks for 3D Segmentation on Point Clouds
University of Southern California
场景语义分割的新型网络结构,主要将rnn加入当网络结构中


Poster:


Attentional ShapeContextNet for Point Cloud Recognition
University of California, San Diego
点云处理的一种新的形式,区别于体素化或者如同pointnet


Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds
Clemson University
Arxiv中的题目为:Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling
切入点类似于pointnet++,针对pointnet中缺失的局部处理,效果优于pointnet++


SO-Net: Self-Organizing Network for Point Cloud Analysis
新加坡国立大学
自组织神经网络在点云数据上的应用


Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Universite Paris-Est
通过superpoint graph捕捉点云结构,支持百万级点云数据的处理


PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
stanford university


A Network Architecture for Point Cloud Classification via Automatic Depth Images Generation
ethz
将点云数据转化为一系列2d深度图像后,喂入训练好的CNNs进行数据分类

Frustum PointNets for 3D Object Detection from RGB-D Data
Standford university
Pointnet原作者文章,主要关注大规模点云下的目标检测问题


PU-Net: Point Cloud Upsampling Network
CUHK & SIAT
数据驱动的点云数据上采样


Pointwise Convolutional Neural Networks
The University of Tokyo
Pointwise卷积神经网络在点云数据上的应用

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