3D Shape Classification

28 papers with code • 1 benchmarks • 1 datasets

Image: Sun et al

Libraries

Use these libraries to find 3D Shape Classification models and implementations
2 papers
77

Datasets


Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds

meliao/rotation-invariant-random-features 27 Jul 2023

Specifically, we extend the random features method of Rahimi & Recht 2007 by deriving a version that is invariant to three-dimensional rotations and showing that it is fast to evaluate on point cloud data.

3
27 Jul 2023

ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud Understanding

auniquesun/vipformer 25 Mar 2023

For example, the image branch in CrossPoint is $\sim$8. 3x heavier than the point cloud branch leading to higher complexity and latency.

20
25 Mar 2023

MVTN: Learning Multi-View Transformations for 3D Understanding

ajhamdi/mvtorch 27 Dec 2022

Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes.

77
27 Dec 2022

LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers

zhh6425/LocalContextPropagation 23 Oct 2022

Transformer with its underlying attention mechanism and the ability to capture long-range dependencies makes it become a natural choice for unordered point cloud data.

3
23 Oct 2022

PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape Recognition

keeganhk/pointmcd 7 Jul 2022

In this paper, we explore the possibility of boosting deep 3D point cloud encoders by transferring visual knowledge extracted from deep 2D image encoders under a standard teacher-student distillation workflow.

48
07 Jul 2022

Masked Discrimination for Self-Supervised Learning on Point Clouds

haotian-liu/maskpoint 21 Mar 2022

Masked autoencoding has achieved great success for self-supervised learning in the image and language domains.

85
21 Mar 2022

diffConv: Analyzing Irregular Point Clouds with an Irregular View

mmmmimic/diffconvnet 29 Nov 2021

Standard spatial convolutions assume input data with a regular neighborhood structure.

26
29 Nov 2021

DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion

adonis-galaxy/dspoint 19 Nov 2021

We reverse the conventional design of applying convolution on voxels and attention to points.

17
19 Nov 2021

PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation

myavartanoo/PolyNet_PyTorch 15 Oct 2021

3D shape representation and its processing have substantial effects on 3D shape recognition.

17
15 Oct 2021

TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network

prajwalsingh/TreeGCN-ED 7 Oct 2021

Point cloud is one of the widely used techniques for representing and storing 3D geometric data.

9
07 Oct 2021