CVPR 2019——Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds - 代码天地

CVPR 2019——Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

其他 2020-09-18 14:12:55 阅读次数: 0

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转载自blog.csdn.net/Dujing2019/article/details/105184159

CVPR 2019——Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

【CVPR2022 点云3D检测SOTA】SoftGroup for 3D Instance Segmentation on Point Clouds

CVPR 2020——Learning to Segment 3D Point Clouds in 2D Image Space

【点云识别】PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation (CVPR 2020)

CVPR 2020——PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation

【CVPR 2018】Learning Representations and Generative Models for 3D Point Clouds

CVPR 2019——PointConv: Deep Convolutional Networks on 3D Point Clouds

【点云识别】Learning to Segment 3D Point Clouds in 2D Image Space (CVPR 2020)

【CVPR 2017】PointNet：Deep Learning on Point Sets for 3D Classification and Segmentation

CVPR 2019: Generating 3D Adversarial Point Clouds 生成三维对抗点云数据

【论文阅读】[CVPR 2019] PointConv： Deep Convolutional Networks on 3D Point Clouds. [cls. seg.]

Point Attention Network for Semantic Segmentation of 3D Point Clouds 论文解析

Deep Learning for 3D Point Clouds: A Survey

Fast Segmentation of 3D Point Clouds: A Paradigm on LiDAR Data for Autonomous Vehicle Applications阅读

Fast Segmentation of 3D Point Clouds for Ground Vehicles 文章解读

读论文：Real-time Object Classification in 3D Point Clouds Using Point Feature Histograms

【论文简述】Occlusion Guided Scene Flow Estimation on 3D Point Clouds（CVPR 2021）

ECCV2020——Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds

CVPR2020——3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation

CVPR 2020——RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds （已开源）

三维目标检测论文：Deep Hough Voting for 3D Object Detection in Point Clouds

【三维目标检测】VoteNet：Deep Hough Voting for 3D Object Detection in Point Clouds

阅读笔记 Deep Hough Voting for 3D Object Detection in Point Clouds

【论文笔记】PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds

文章解读 -- FlowNet3D：Learning Scene Flow in 3D Point Clouds

Paper5：Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Per

CVPR 2020——OccuSeg: Occupancy-aware 3D Instance Segmentation

三维点云语义分割【综述】 ——Deep Learning for 3D Point Clouds: A Survey

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds 笔记

【论文阅读】【综述】Deep Learning for 3D Point Clouds: A Survey

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