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3D Part Segmentation

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Segmenting 3D object parts

<span style="color:grey; opacity: 0.6">( Image credit: MeshCNN: A Network with an Edge )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Ayumu-J-S/Point-JEPA

공식 코드

Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud

https://github.com/Colin97/PartSLIP_page

공식 코드

PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models

https://github.com/DylanWusee/pointconv

공식 코드

PointConv: Deep Convolutional Networks on 3D Point Clouds

https://github.com/HaochengWan/PVT

공식 코드

PVT: Point-Voxel Transformer for Point Cloud Learning

https://github.com/HuguesTHOMAS/KPConv

공식 코드

KPConv: Flexible and Deformable Convolution for Point Clouds

https://github.com/JunweiZheng93/APES

공식 코드

Attention-based Point Cloud Edge Sampling

https://github.com/KAIST-Visual-AI-Group/PartSTAD

공식 코드

PartSTAD: 2D-to-3D Part Segmentation Task Adaptation

https://github.com/KangchengLiu/Feature-Geometric-Net-FG-Net

공식 코드

FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling

https://github.com/MenghaoGuo/PCT

공식 코드

PCT: Point cloud transformer

https://github.com/Meowuu7/AutoGPart

공식 코드

AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation

https://github.com/OATML/Non-Parametric-Transformers

공식 코드

Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning

https://github.com/Pang-Yatian/Point-MAE

공식 코드

Masked Autoencoders for Point Cloud Self-supervised Learning

https://github.com/Pointcept/Pointcept

공식 코드

Point Transformer

https://github.com/ShiQiu0419/DRNet

공식 코드

Dense-Resolution Network for Point Cloud Classification and Segmentation

https://github.com/WangYueFt/dgcnn

공식 코드

Dynamic Graph CNN for Learning on Point Clouds

https://github.com/Yochengliu/DensePoint

공식 코드

DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing

https://github.com/Yochengliu/Relation-Shape-CNN

공식 코드

Relation-Shape Convolutional Neural Network for Point Cloud Analysis

https://github.com/aboulch/ConvPoint

공식 코드

ConvPoint: Continuous Convolutions for Point Cloud Processing

https://github.com/adonis-galaxy/dspoint

공식 코드

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

https://github.com/ajhamdi/vointcloud

공식 코드

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

https://github.com/amrinkareem/paris3d

공식 코드

PARIS3D: Reasoning-based 3D Part Segmentation Using Large Multimodal Model

https://github.com/ardianumam/partdistill

공식 코드

PartDistill: 3D Shape Part Segmentation by Vision-Language Model Distillation

https://github.com/brown-ivl/ConDor

공식 코드

ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes

https://github.com/crane-papercode/3dmedpt

공식 코드

3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis

https://github.com/cyysc1998/3D-Pretraining

공식 코드

Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes

https://github.com/engelnico/point-transformer

공식 코드

Point Transformer

https://github.com/facebookresearch/SparseConvNet

공식 코드

Submanifold Sparse Convolutional Networks

https://github.com/fsemerar/slicertomosam

공식 코드

TomoSAM: a 3D Slicer extension using SAM for tomography segmentation

https://github.com/guochengqian/assanet

공식 코드

ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning

https://github.com/guochengqian/openpoints/blob/master/models/backbone/pointvector.py

공식 코드

PointVector: A Vector Representation In Point Cloud Analysis

https://github.com/guochengqian/pointnext

공식 코드

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

https://github.com/haydenyu/mm-point

공식 코드

MM-Point: Multi-View Information-Enhanced Multi-Modal Self-Supervised 3D Point Cloud Understanding

https://github.com/hlei-ziyan/SPH3D-GCN

공식 코드

Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds

https://github.com/isunchy/3d_instance_segmentation

공식 코드

Semantic Segmentation-Assisted Instance Feature Fusion for Multi-Level 3D Part Instance Segmentation

https://github.com/ituvisionlab/ODFNet

공식 코드

ODFNet: Using orientation distribution functions to characterize 3D point clouds

https://github.com/jiamang/ibt

공식 코드

Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation

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