Browse SoTA > Computer Vision > 3D > 3D Object Classification

3D Object Classification

12 papers with code · Computer Vision
Subtask of 3D

Benchmarks

Greatest papers with code

MeshCNN: A Network with an Edge

16 Sep 2018ranahanocka/MeshCNN

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.

3D PART SEGMENTATION CUBE ENGRAVING 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 OBJECT CLASSIFICATION

RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints

CVPR 2018 kanezaki/rotationnet

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

FPConv: Learning Local Flattening for Point Convolution

CVPR 2020 lyqun/FPConv

We introduce FPConv, a novel surface-style convolution operator designed for 3D point cloud analysis.

3D OBJECT CLASSIFICATION OBJECT CLASSIFICATION SCENE SEGMENTATION

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 OBJECT CLASSIFICATION UNSUPERVISED REPRESENTATION LEARNING

Learning a Hierarchical Latent-Variable Model of 3D Shapes

17 May 2017lorenmt/vsl

We propose the Variational Shape Learner (VSL), a generative model that learns the underlying structure of voxelized 3D shapes in an unsupervised fashion.

3D OBJECT CLASSIFICATION 3D OBJECT RECOGNITION 3D RECONSTRUCTION 3D SHAPE GENERATION

Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

10 Jan 2019Daniel-Liu-c0deb0t/3D-Neural-Network-Adversarial-Attacks

We present a preliminary evaluation of adversarial attacks on deep 3D point cloud classifiers, namely PointNet and PointNet++, by evaluating both white-box and black-box adversarial attacks that were proposed for 2D images and extending those attacks to reduce the perceptibility of the perturbations in 3D space.

3D OBJECT CLASSIFICATION IMAGE CLASSIFICATION OBJECT CLASSIFICATION