3D Object Classification

43 papers with code • 3 benchmarks • 6 datasets

3D Object Classification is the task of predicting the class of a 3D object point cloud. It is a voxel level prediction where each voxel is classified into a category. The popular benchmark for this task is the ModelNet dataset. The models for this task are usually evaluated with the Classification Accuracy metric.

Image: Sedaghat et al

Most implemented papers

Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds

hlei-ziyan/SPH3D-GCN 20 Sep 2019

We propose a spherical kernel for efficient graph convolution of 3D point clouds.

Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud

mutianxu/GDANet 20 Dec 2020

GDANet introduces Geometry-Disentangle Module to dynamically disentangle point clouds into the contour and flat part of 3D objects, respectively denoted by sharp and gentle variation components.

PointLLM: Empowering Large Language Models to Understand Point Clouds

openrobotlab/pointllm 31 Aug 2023

The unprecedented advancements in Large Language Models (LLMs) have shown a profound impact on natural language processing but are yet to fully embrace the realm of 3D understanding.

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

mys007/ecc CVPR 2017

A number of problems can be formulated as prediction on graph-structured data.

3D Point Capsule Networks

yongheng1991/3D-point-capsule-networks CVPR 2019

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.

Point Transformer

engelnico/point-transformer 2 Nov 2020

In this work, we present Point Transformer, a deep neural network that operates directly on unordered and unstructured point sets.

SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

ShunChengWu/SceneGraphFusion CVPR 2021

Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks.

PointMixer: MLP-Mixer for Point Cloud Understanding

lifebeyondexpectations/eccv22-pointmixer 22 Nov 2021

MLP-Mixer has newly appeared as a new challenger against the realm of CNNs and transformer.

Uni3D: Exploring Unified 3D Representation at Scale

baaivision/uni3d 10 Oct 2023

Scaling up representations for images or text has been extensively investigated in the past few years and has led to revolutions in learning vision and language.

Open-Pose 3D Zero-Shot Learning: Benchmark and Challenges

weiguangzhao/diff-op3d 12 Dec 2023

To this end, we propose a more realistic and challenging scenario named open-pose 3D zero-shot classification, focusing on the recognition of 3D objects regardless of their orientation.