3D Part Segmentation
64 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
PARIS3D: Reasoning-based 3D Part Segmentation Using Large Multimodal Model
We introduce a novel segmentation task known as reasoning part segmentation for 3D objects, aiming to output a segmentation mask based on complex and implicit textual queries about specific parts of a 3D object.
MM-Point: Multi-View Information-Enhanced Multi-Modal Self-Supervised 3D Point Cloud Understanding
In perception, multiple sensory information is integrated to map visual information from 2D views onto 3D objects, which is beneficial for understanding in 3D environments.
PartSLIP++: Enhancing Low-Shot 3D Part Segmentation via Multi-View Instance Segmentation and Maximum Likelihood Estimation
zyc00/partslip2
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Open-world 3D part segmentation is pivotal in diverse applications such as robotics and AR/VR.
Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features
niladridutt/Diffusion-3D-Features
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We present Diff3F as a simple, robust, and class-agnostic feature descriptor that can be computed for untextured input shapes (meshes or point clouds).
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation
mr-neko/jm3d
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Insufficient synergy neglects the idea that a robust 3D representation should align with the joint vision-language space, rather than independently aligning with each modality.
Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models
In this paper, we propose a novel 3D-to-2D generative pre-training method that is adaptable to any point cloud model.
TomoSAM: a 3D Slicer extension using SAM for tomography segmentation
TomoSAM has been developed to integrate the cutting-edge Segment Anything Model (SAM) into 3D Slicer, a highly capable software platform used for 3D image processing and visualization.
Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation
jiamang/ibt
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Discovering inter-point connection for efficient high-dimensional feature extraction from point coordinate is a key challenge in processing point cloud.
Self-positioning Point-based Transformer for Point Cloud Understanding
In this paper, we present a Self-Positioning point-based Transformer (SPoTr), which is designed to capture both local and global shape contexts with reduced complexity.
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.
