QingyongHu/SoTA-Point-Cloud
Academic survey paper published in IEEE TPAMI reviewing deep learning methods for 3D point cloud analysis.

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This repository hosts the official implementation and materials for a survey paper covering deep learning approaches for 3D point clouds. It reviews methods across major tasks including 3D shape classification, 3D object detection, and 3D point cloud segmentation. The survey provides comparative results on public datasets and presents taxonomy organizing the field, serving as a reference for researchers in 3D computer vision and deep learning.