PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
翻译 - PointNet 和 PointNet++ 由 pytorch（纯 python）在 ModelNet、ShapeNet 和 S3DIS 上实现。
#计算机科学#Pytorch framework for doing deep learning on point clouds.
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)
[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
[CVPR 2022 Oral] SoftGroup for Instance Segmentation on 3D Point Clouds
[CVPR 2022 Oral] Official implementation for "Surface Representation for Point Clouds"
[ECCV2022] FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection
#计算机科学#[CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
Grid-GCN for Fast and Scalable Point Cloud Learning
Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'
[ICIP2023] TR3D: Towards Real-Time Indoor 3D Object Detection
[WACV'24] TD3D: Top-Down Beats Bottom-Up in 3D Instance Segmentation
CVPR 2020, "FPConv: Learning Local Flattening for Point Convolution"
PVT: Point-Voxel Transformer for 3D Deep Learning
[AAAI2025] UniDet3D: Multi-dataset Indoor 3D Object Detection
[ICCV-23] Official implementation of SeedAL for seeding active learning for 3D semantic segmentation
[CVPR 2021] CGA-Net: Category Guided Aggregation for Point Cloud Semantic Segmentation
#计算机科学#PyTorch implementation to train MortonNet and use it to compute point features. MortonNet is trained in a self-supervised fashion, and the features can be used for general tasks like part or semantic ...
