ZicaiFeng

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

Cluster3DSeg. This is the official implementation of "Clustering based Point Cloud Representation Learning for 3D Analysis" (Accepted at ICCV 2023).

3D-Point-Cloud-Get-Started. This summary includes traditional algorithms and deep learning methods, which refers to paper with code, shenlanxueyuan, and My blog (in Chinese).

AwesomeWMAD. This repository contains a curated list of resources related to World Models for Autonomous Driving (WMAD), based on the survey.

Shape-Measure. PyTorch version of shape evaluation metrics

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

S2S. This is the official implementation of "Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data" (Accepted at ECCV 2024).

Deecamp2020-Point-Cloud-Multi-Object-Tracking. This is my implementation of the LIDAR target detection track of DEECAMP 2020. The tracking process occurs after the object detection.

GWM.

WMAD-Benchmarks.

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

fengzicai.