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3D Shape Classification

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Showing 1–50 of 82 papers

TitleStatusHype
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point CloudsCode1
Ensemble Quadratic Assignment Network for Graph Matching—0
Invariant Training 2D-3D Joint Hard Samples for Few-Shot Point Cloud Recognition—0
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point CloudsCode0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding—0
ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud UnderstandingCode1
Frequency-domain Learning for Volumetric-based 3D Data Perception—0
Robust 3D Shape Classification via Non-Local Graph Attention Network—0
Rethinking Rotation Invariance with Point Cloud Registration—0
MVTN: Learning Multi-View Transformations for 3D UnderstandingCode1
LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in TransformersCode0
PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape RecognitionCode1
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons—0
Masked Discrimination for Self-Supervised Learning on Point CloudsCode1
diffConv: Analyzing Irregular Point Clouds with an Irregular ViewCode1
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds—0
DSPoint: Dual-scale Point Cloud Recognition with High-frequency FusionCode1
PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape RepresentationCode1
TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph NetworkCode0
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views—0
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning—0
POINTVIEW-GCN: 3D SHAPE CLASSIFICATION WITH MULTI-VIEW POINT CLOUDSCode1
Spatio-temporal Self-Supervised Representation Learning for 3D Point CloudsCode1
Point Cloud Learning with Transformer—0
Potential Convolution: Embedding Point Clouds into Potential Fields—0
Learning Equivariant RepresentationsCode1
MVTN: Multi-View Transformation Network for 3D Shape RecognitionCode1
RocNet: Recursive Octree Network for Efficient 3D Deep Representation—0
Learning Attentive and Hierarchical Representations for 3D Shape Recognition—0
Unsupervised Deep Shape Descriptor With Point Distribution LearningCode0
View-GCN: View-Based Graph Convolutional Network for 3D Shape AnalysisCode1
Fine-Grained 3D Shape Classification with Hierarchical Part-View AttentionsCode1
Extending DeepSDF for automatic 3D shape retrieval and similarity transform estimation—0
Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges—0
Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences—0
Shape retrieval of non-rigid 3d human models—0
Deep Learning for 3D Point Clouds: A SurveyCode1
Enhancing 2D Representation via Adjacent Views for 3D Shape Retrieval—0
A Topological Nomenclature for 3D Shape Analysis in ConnectomicsCode0
HRGE-Net: Hierarchical Relational Graph Embedding Network for Multi-view 3D Shape Recognition—0
View N-gram Network for 3D Object Retrieval—0
Rethinking Loss Design for Large-scale 3D Shape Retrieval—0
Re-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification—0
Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing—0
Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks—0
Equivariant Multi-View NetworksCode0
Non-rigid 3D shape retrieval based on multi-view metric learning—0
A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning—0
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