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1. Cluster3DSeg Cluster3DSeg Public

   This is the official implementation of "Clustering based Point Cloud Representation Learning for 3D Analysis" (Accepted at ICCV 2023).

   Python 33 1

2. LSK3DNet LSK3DNet Public

   This is the official implementation of "LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels" (Accepted at CVPR 2024).

   23 3

3. Interpretable3D Interpretable3D Public

   This is the official implementation of "Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point Clouds" (Accepted at AAAI 2024).

   Python 5 1

4. Re-Track Re-Track Public

   This is the implementation of "A Novel Object Re-Track Framework for 3D Point Clouds", which is accepted by ACM-MM 2020.

   Python 2

5. 3D-Point-Cloud-Get-Started 3D-Point-Cloud-Get-Started Public

   This summary includes traditional algorithms and deep learning methods, which refers to paper with code, shenlanxueyuan, and My blog (in Chinese).

   31 2

6. Shape-Measure Shape-Measure Public

   PyTorch version of shape evaluation metrics

   Cuda 25 3