[Paper Reading] Summary of 3D Point Cloud Papers - Code World

[Paper Reading] Summary of 3D Point Cloud Papers

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Origin blog.csdn.net/weixin_43154149/article/details/123407341

[Paper Reading] Summary of 3D Point Cloud Papers

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[3D point cloud] weakly supervised point cloud segmentation (paper interpretation CVPR2020)

Interpretation of the paper | Point comparison: 3D point cloud understanding unsupervised pre-training

Paper reading | PointNet, a neural network that can directly process disordered 3D point clouds

Paper reading: EPNet: Enhancing Point Features with ImageSemantics for 3D Object Detection

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Interpretation of the paper | Point cloud segmentation of 3D scattered parts based on RealSense

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[Paper Reading][CVPR 2022] ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversaria

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Paper Reading-1: Building Graph Cut Optimization Extraction Method Fused with LiDAR Point Cloud and Orthophoto 2018

[Paper reading] Multi-period vehicle-mounted laser point cloud registration using road target features

"Paper Reading 19" Multisource forest point cloud registration with semantic-guided keypoints and robust RANSAC

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[Paper reading] Intensive reading of time series motion detection papers (2018)

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[Paper reading] Critical analysis of 3D reconstruction based on NeRF

CVPR2020 article summary | point cloud processing, 3D reconstruction, pose estimation, SLAM, 3D data set, etc. (12 articles)

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