3D Classification

35 papers with code • 0 benchmarks • 12 datasets

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Libraries

Use these libraries to find 3D Classification models and implementations
3 papers
79

Most implemented papers

Learning SO(3) Equivariant Representations with Spherical CNNs

daniilidis-group/spherical-cnn ECCV 2018

We address the problem of 3D rotation equivariance in convolutional neural networks.

PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

guochengqian/pointnext 9 Jun 2022

In this work, we revisit the classical PointNet++ through a systematic study of model training and scaling strategies, and offer two major contributions.

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

minzhang-1/PointHop2 9 Feb 2020

The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.

MVTN: Multi-View Transformation Network for 3D Shape Recognition

ajhamdi/MVTN ICCV 2021

MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.

Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

IDU-CVLab/COV19D 22 Nov 2021

Secondly, the original dataset was processed via anatomy-relevant masking of slice, removing none-representative slices from the CT volume, and hyperparameters tuning.

Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding

ajhamdi/vointcloud 30 Nov 2021

To this end, we introduce the concept of the multi-view point cloud (Voint cloud), representing each 3D point as a set of features extracted from several view-points.

PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning

yangyangyang127/pointclip_v2 ICCV 2023

In this paper, we first collaborate CLIP and GPT to be a unified 3D open-world learner, named as PointCLIP V2, which fully unleashes their potential for zero-shot 3D classification, segmentation, and detection.

Robustifying Point Cloud Networks by Refocusing

yossilevii100/refocusing 10 Aug 2023

In this study, we develop a general mechanism to increase neural network robustness based on focus analysis.

3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models

dkoguciuk/ensemble_learning_for_point_clouds 17 Apr 2019

In this study, we present an analysis of model-based ensemble learning for 3D point-cloud object classification and detection.