Benchmarks
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Subtasks
Greatest papers with code
MeshCNN: A Network with an Edge
In this paper, we utilize the unique properties of the mesh for a direct analysis of 3D shapes using MeshCNN, a convolutional neural network designed specifically for triangular meshes.
O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
• Microsoft/O-CNN
• 
We present O-CNN, an Octree-based Convolutional Neural Network (CNN) for 3D shape analysis.
Ranked #2 on
3D Object Classification
on ModelNet40
OctNet: Learning Deep 3D Representations at High Resolutions
We present OctNet, a representation for deep learning with sparse 3D data.
3D OBJECT CLASSIFICATION CLASSIFICATION OBJECT CLASSIFICATION
3D Point Capsule Networks
CVPR 2019
• yongheng1991/3D-point-capsule-networks
• 
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data.
Ranked #3 on
3D Object Classification
on ModelNet40
3D FEATURE MATCHING 3D GEOMETRY PERCEPTION 3D OBJECT CLASSIFICATION 3D OBJECT RECONSTRUCTION 3D PART SEGMENTATION 3D POINT CLOUD MATCHING 3D SHAPE GENERATION 3D SHAPE REPRESENTATION CLASSIFICATION
A Graph-CNN for 3D Point Cloud Classification
• maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification
•
Graph convolutional neural networks (Graph-CNNs) extend traditional CNNs to handle data that is supported on a graph.
3D OBJECT CLASSIFICATION 3D POINT CLOUD CLASSIFICATION CLASSIFICATION OBJECT CLASSIFICATION POINT CLOUD CLASSIFICATION
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
We propose a spherical kernel for efficient graph convolution of 3D point clouds.
Ranked #2 on
3D Object Classification
on ModelNet40
3D INSTANCE SEGMENTATION 3D OBJECT CLASSIFICATION 3D PART SEGMENTATION POINT CLOUD CLASSIFICATION
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
ICCV 2019
• hkust-vgd/scanobjectnn
•
From our comprehensive benchmark, we show that our dataset poses great challenges to existing point cloud classification techniques as objects from real-world scans are often cluttered with background and/or are partial due to occlusions.
3D OBJECT CLASSIFICATION 3D POINT CLOUD CLASSIFICATION CLASSIFICATION OBJECT CLASSIFICATION POINT CLOUD CLASSIFICATION
FPConv: Learning Local Flattening for Point Convolution
We introduce FPConv, a novel surface-style convolution operator designed for 3D point cloud analysis.
3D OBJECT CLASSIFICATION OBJECT CLASSIFICATION SCENE SEGMENTATION
RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints
We propose a Convolutional Neural Network (CNN)-based model "RotationNet," which takes multi-view images of an object as input and jointly estimates its pose and object category.
3D OBJECT CLASSIFICATION OBJECT CLASSIFICATION POSE ESTIMATION
Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
CVPR 2020
• raoyongming/PointGLR
•
Based on this hypothesis, we propose to learn point cloud representation by bidirectional reasoning between the local structures at different abstraction hierarchies and the global shape without human supervision.
3D OBJECT CLASSIFICATION CLASSIFICATION OBJECT CLASSIFICATION UNSUPERVISED REPRESENTATION LEARNING