3D Classification
20 papers with code • 1 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in 3D Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
ShapeNetCore
ModelNet40-C
COV19-CT-DB
Corn Seeds Dataset
InfiniteRep
Subtasks
Most implemented papers
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
charlesq34/pointnet
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CVPR 2017
Point cloud is an important type of geometric data structure.
Learning SO(3) Equivariant Representations with Spherical CNNs
daniilidis-group/spherical-cnn
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ECCV 2018
We address the problem of 3D rotation equivariance in convolutional neural networks.
PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification
The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models
dkoguciuk/ensemble_learning_for_point_clouds
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In this study, we present an analysis of model-based ensemble learning for 3D point-cloud object classification and detection.
Enhancing Learnability of classification algorithms using simple data preprocessing in fMRI scans of Alzheimer's disease
Alzheimer's Disease (AD) is the most common type of dementia.
Triangle-Net: Towards Robustness in Point Cloud Learning
Previous research has shown that points' sparsity, rotation and positional inherent variance can lead to a significant drop in the performance of point cloud based classification techniques.
Convolution in the Cloud: Learning Deformable Kernels in 3D Graph Convolution Networks for Point Cloud Analysis
j1a0m0e4sNTU/3dgcn
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CVPR 2020
Point clouds are among the popular geometry representations for 3D vision applications.
MeshWalker: Deep Mesh Understanding by Random Walks
Each walk is organized as a list of vertices, which in some manner imposes regularity on the mesh.
Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features
Second, segmentation and classification models are connected with two different feature aggregation strategies to enhance the classification performance.
MVTN: Multi-View Transformation Network for 3D Shape Recognition
MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.
