QingyongHu / SensatUrban
π₯Urban-scale point cloud dataset (CVPR 2021 & IJCV 2022)
β524Updated 2 years ago
Alternatives and similar repositories for SensatUrban:
Users that are interested in SensatUrban are comparing it to the libraries listed below
- PyTorch implementation of RandLA-Netβ372Updated 3 years ago
- PointGroup: Dual-Set Point Grouping for 3D Instance Segmentationβ416Updated 8 months ago
- A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadwaysβ245Updated 10 months ago
- Kernel Point Convolutionsβ743Updated 4 years ago
- Kernel Point Convolution implemented in PyTorchβ822Updated 4 months ago
- Large-scale Point Cloud Semantic Segmentation with Superpoint Graphsβ769Updated last year
- π₯RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)β1,388Updated last year
- Pytorch framework for doing deep learning on point clouds.β236Updated 3 years ago
- [ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolutionβ597Updated 9 months ago
- RandLA-Net's implementation with Pytorchβ130Updated 4 years ago
- β191Updated 3 years ago
- [CVPR 2022 Oral] SoftGroup for Instance Segmentation on 3D Point Cloudsβ375Updated last year
- A faster implementation of PointNet++ based on PyTorch.β496Updated 2 years ago
- Fully Convolutional Geometric Features: Fast and accurate 3D features for registration and correspondence.β666Updated 4 years ago
- Pytorch Implementation of RandLA-Net (https://arxiv.org/abs/1911.11236)β134Updated 2 years ago
- Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)β394Updated 2 years ago
- Differentiable Point Cloud Sampling (CVPR 2020 Oral)β380Updated last year
- [NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategiesβ865Updated last year
- This is an unofficial implementation of the Point Transformer paper.β564Updated 3 years ago
- Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)β880Updated 2 years ago
- [CVPR 2021] SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registrationβ284Updated 3 years ago
- Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Traβ¦β763Updated last month
- (TPAMI2023) Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Surveyβ208Updated 2 years ago
- SemanticKITTI API for visualizing dataset, processing data, and evaluating results.β829Updated 2 weeks ago
- Semantic3D segmentation with Open3D and PointNet++β533Updated 8 months ago
- [NeurIPS'22] An official PyTorch implementation of PTv2.β380Updated last year
- [CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.β534Updated 2 months ago
- π₯[IEEE TPAMI 2020] Deep Learning for 3D Point Clouds: A Surveyβ1,606Updated 3 years ago
- (CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Cloudsβ296Updated last year
- This is a complete package of recent deep learning methods for 3D point clouds in pytorch (with pretrained models).β791Updated 3 weeks ago