Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation
Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation
Non-rigid Point Cloud Registration with Neural Deformation Pyramid
Non-rigid Point Cloud Registration with Neural Deformation Pyramid
Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds (CVPR2022)
Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds (CVPR2022)
Neural Points: Point Cloud Representation with Neural Fields
Neural Points: Point Cloud Representation with Neural Fields
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation
Point-NeRF: Point-based Neural Radiance Fields
Point-NeRF: Point-based Neural Radiance Fields
Geometric Transformer for Fast and Robust Point Cloud Registration
Geometric Transformer for Fast and Robust Point Cloud Registration
Blender 3.1 Alpha (and later) PLY importer that correctly loads point clouds (and all PLY models as point clouds)
Blender 3.1 PLY importer that correctly loads point clouds (and all PLY models as point clouds)
Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions
Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions
Benchmarking and Analyzing Point Cloud Classification under Corruptions
Benchmarking and Analyzing Point Cloud Classification under Corruptions
A static features classifier for Point-Could clusters using an Attention-RNN model
A static features classifier for Point-Could clusters using an Attention-RNN model
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition 2022)
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition 2022)
HRegNet: A Hierarchical Network for Efficient and Accurate Outdoor LiDAR Point Cloud Registration
HRegNet: A Hierarchical Network for Efficient and Accurate Outdoor LiDAR Point Cloud Registration
Attention-based Transformation from Latent Features to Point Clouds (AAAI 2022)
Attention-based Transformation from Latent Features to Point Clouds (AAAI 2022)
UnpNet: Rethinking 3-D LiDAR Point Cloud Segmentation(IEEE TNNLS)
UnpNet: Rethinking 3-D LiDAR Point Cloud Segmentation(IEEE TNNLS)
Given a 2D triangle mesh, we could randomly generate cloud points that fill in the triangle mesh
Given a 2D triangle mesh, we could randomly generate cloud points that fill in the triangle mesh
Self-Adaptable Point Processes with Nonparametric Time Decays
Self-Adaptable Point Processes with Nonparametric Time Decays
Get 2D point positions (e.g., facial landmarks) projected on 3D mesh
Get 2D point positions (e.g., facial landmarks) projected on 3D mesh
Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences
Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation
Fast and robust clustering of point clouds generated with a Velodyne sensor
Fast and robust clustering of point clouds generated with a Velodyne sensor
A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar
A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar
Pre-Training 3D Point Cloud Transformers with Masked Point Modeling
Pre-Training 3D Point Cloud Transformers with Masked Point Modeling
Jittor implementation of PCT:Point Cloud Transformer
Jittor implementation of PCT:Point Cloud Transformer
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D
SpConv: Spatially Sparse Convolution Library
SpConv: Spatially Sparse Convolution Library
PCRNet: Point Cloud Registration Network using PointNet Encoding
PCRNet: Point Cloud Registration Network using PointNet Encoding
DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion
DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion
Some method of processing point cloud
Some method of processing point cloud
Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation
Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation
Multimodal Virtual Point 3D Detection
Multimodal Virtual Point 3D Detection
Weakly Supervised 3D Object Detection from Point Cloud with Only Image Level Annotation
Weakly Supervised 3D Object Detection from Point Cloud with Only Image Level Annotation
Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation
Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation
Pytorch implementation of Straight Sampling Network For Point Cloud Learning
Pytorch implementation of Straight Sampling Network For Point Cloud Learning
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration
Automatically scale a 3D model/mesh/point cloud on Agisoft Metashape
Automatically scale a 3D model/mesh/point cloud on Agisoft Metashape
Cascading Feature Extraction for Fast Point Cloud Registration
Cascading Feature Extraction for Fast Point Cloud Registration
A tool to allow New World players to calculate the best place to put their Attribute Points for their build and level
A tool to allow New World players to calculate the best place to put their Attribute Points for their build and level
SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection
SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
Dynamic Graph CNN for Learning on Point Clouds
Dynamic Graph CNN for Learning on Point Clouds
PyTorch implementation for View-Guided Point Cloud Completion
PyTorch implementation for View-Guided Point Cloud Completion
An inofficial PyTorch implementation of PREDATOR based on KPConv
An inofficial PyTorch implementation of PREDATOR based on KPConv
Point Cloud Registration using Representative Overlapping Points
Point Cloud Registration using Representative Overlapping Points
TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction
TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction
Point cloud processing tool library can be used to process point clouds, 3d meshes, and voxels
This point cloud processing tool library can be used to process point clouds, 3d meshes, and voxels.
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds