Alternatives and similar repositories for 3D-Point-Cloud-Learning

Users that are interested in 3D-Point-Cloud-Learning are comparing it to the libraries listed below

• NUAAXQ / MLCVNet
  [CVPR 2020] MLCVNet: Multi-Level Context VoteNet for 3D Object Detection
  ☆123Updated 3 years ago
• Zhang-VISLab / Learning-to-Segment-3D-Point-Clouds-in-2D-Image-Space
  ☆208Updated 2 years ago
• xingyul / meteornet
  MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences (ICCV 2019 Oral)
  ☆156Updated 3 years ago
• liruihui / PointAugment
  Code for PointAugment: an Auto-Augmentation Framework for Point Cloud Classification, CVPR 2020 (Oral)
  ☆217Updated 4 years ago
• facebookresearch / imvotenet
  ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image Votes
  ☆133Updated 2 years ago
• hzykent / JSENet
  Implementation of ECCV2020 paper - JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds
  ☆132Updated 4 years ago
• dlinzhao / JSNet
  JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds, AAAI2020
  ☆105Updated 5 years ago
• DylanWusee / PointPWC
  PointPWC-Net is a deep coarse-to-fine network designed for 3D scene flow estimation from 3D point clouds.
  ☆159Updated 4 years ago
• Xharlie / Grid-GCN
  Grid-GCN for Fast and Scalable Point Cloud Learning
  ☆185Updated 5 years ago
• fly519 / ELGS
  Code for the paper: Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations
  ☆51Updated 4 years ago
• Shathe / 3D-MiniNet
  Official Implementation in Pytorch and Tensorflow of 3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D…
  ☆181Updated 2 years ago
• waterljwant / SSC
  Semantic Scene Completion
  ☆108Updated 5 years ago
• hszhao / PointWeb
  PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing, CVPR2019.
  ☆210Updated 5 years ago
• aim-uofa / DyCo3D
  ☆125Updated 2 years ago
• LiuShihHung / GICN
  ☆52Updated 5 years ago
• maxjaritz / mvpnet
  Implementation of the paper "Multi-view PointNet for 3D Scene Understanding"
  ☆83Updated 5 years ago
• XuyangBai / KPConv.pytorch
  PyTorch reimplementation for "KPConv: Flexible and Deformable Convolution for Point Clouds" https://arxiv.org/abs/1904.08889
  ☆70Updated 5 years ago
• hongfz16 / DS-Net
  [CVPR 2021/TPAMI 2023] Rank 1st in the public leaderboard of SemanticKITTI Panoptic Segmentation (2020-11-16)
  ☆249Updated 3 years ago
• laoreja / HPLFlowNet
  Code for our CVPR 2019 paper, HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Cloud…
  ☆110Updated 4 years ago
• kargarisaac / PointNet-SemSeg-VKITTI3D
  VKITTI3D semantic segmentation using PointNet
  ☆34Updated 7 years ago
• MehmetAygun / 4D-PLS
  4D Panoptic Lidar Segmentation
  ☆158Updated last year
• wangyida / softpool
  SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification - ECCV 2020 oral
  ☆77Updated 3 years ago
• yanx27 / JS3C-Net
  Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion (AAAI 2021)
  ☆223Updated 4 years ago
• lijx10 / PCLKeypoints
  Python wrapper for some point cloud keypoint detectors of PCL, including ISS, Harris3D, SIFT3D
  ☆90Updated 4 years ago
• yanx27 / PointASNL
  PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling （CVPR 2020）
  ☆265Updated 4 years ago
• daveredrum / Pointnet2.ScanNet
  PointNet++ Semantic Segmentation on ScanNet in PyTorch with CUDA acceleration
  ☆150Updated 2 years ago
• torch-points3d / torch-points-kernels
  Pytorch kernels for spatial operations on point clouds
  ☆101Updated this week
• hkust-vgd / shellnet
  ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics
  ☆87Updated 6 years ago
• mathieuorhan / pointnet2_semantic
  A pointnet++ fork, with focus on semantic segmentation of differents datasets
  ☆78Updated 7 years ago
• VisualComputingInstitute / vkitti3D-dataset
  ☆107Updated 7 years ago