3D Part Segmentation
65 papers with code • 2 benchmarks • 6 datasets
Segmenting 3D object parts
( Image credit: MeshCNN: A Network with an Edge )
Libraries
Use these libraries to find 3D Part Segmentation models and implementations
ShapeNet
IntrA
LiDAR-MOS
Teeth3DS
Workshop Tools Dataset
TomoSAM
Latest papers
Point2Vec for Self-Supervised Representation Learning on Point Clouds
Recently, the self-supervised learning framework data2vec has shown inspiring performance for various modalities using a masked student-teacher approach.
Attention-based Point Cloud Edge Sampling
JunweiZheng93/APES
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CVPR 2023
Point cloud sampling is a less explored research topic for this data representation.
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models
amrinkareem/paris3d
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CVPR 2023
Generalizable 3D part segmentation is important but challenging in vision and robotics.
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
zrrskywalker/pointclip
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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.
SageMix: Saliency-Guided Mixup for Point Clouds
mlvlab/SageMix
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Mixup is a simple and widely-used data augmentation technique that has proven effective in alleviating the problems of overfitting and data scarcity.
Teeth3DS: a benchmark for teeth segmentation and labeling from intra-oral 3D scans
Teeth segmentation and labeling are critical components of Computer-Aided Dentistry (CAD) systems.
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation
Second, we experimentally observe and verify the edge enhancement and suppression behavior.
Semantic Segmentation-Assisted Instance Feature Fusion for Multi-Level 3D Part Instance Segmentation
isunchy/3d_instance_segmentation
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Our method exploits semantic segmentation to fuse nonlocal instance features, such as center prediction, and further enhances the fusion scheme in a multi- and cross-level way.
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
wangzy22/P2P
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Nowadays, pre-training big models on large-scale datasets has become a crucial topic in deep learning.
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
In this work, we revisit the classical PointNet++ through a systematic study of model training and scaling strategies, and offer two major contributions.
