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3D Object Recognition

3D object recognition is the task of recognising objects from 3D data.

Note that there are related tasks you can look at, such as 3D Object Detection which have more leaderboards.

(Image credit: Look Further to Recognize Better)

Papers

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Showing 51–97 of 97 papers

TitleStatusHype
Investigating the Importance of Shape Features, Color Constancy, Color Spaces and Similarity Measures in Open-Ended 3D Object Recognition—0
Variable-Viewpoint Representations for 3D Object Recognition—0
Interactive Open-Ended Learning for 3D Object Recognition—0
L3DOC: Lifelong 3D Object Classification—0
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance—0
BlenderProcCode2
Learning Relationships for Multi-View 3D Object Recognition—0
Task-Aware Monocular Depth Estimation for 3D Object DetectionCode0
Look Further to Recognize Better: Learning Shared Topics and Category-Specific Dictionaries for Open-Ended 3D Object Recognition—0
SceneGraphNet: Neural Message Passing for 3D Indoor Scene AugmentationCode2
Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images—0
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects—0
A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching—0
MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks—0
Dominant Set Clustering and Pooling for Multi-View 3D Object RecognitionCode0
Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images—0
ClusterNet: Deep Hierarchical Cluster Network With Rigorously Rotation-Invariant Representation for Point Cloud Analysis—0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers—0
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning ModelsCode0
OrthographicNet: A Deep Transfer Learning Approach for 3D Object Recognition in Open-Ended DomainsCode0
Volumetric Convolution: Automatic Representation Learning in Unit Ball—0
Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions—0
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape RecognitionCode0
Multi-View Harmonized Bilinear Network for 3D Object Recognition—0
Multi-level 3D CNN for Learning Multi-scale Spatial FeaturesCode0
Performance Evaluation of 3D Correspondence Grouping Algorithms—0
Triplet-Center Loss for Multi-View 3D Object RetrievalCode0
Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled HolesCode0
Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition—0
Learning a Hierarchical Latent-Variable Model of 3D ShapesCode0
Signature of Geometric Centroids for 3D Local Shape Description and Partial Shape Matching—0
Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition—0
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingCode0
FusionNet: 3D Object Classification Using Multiple Data Representations—0
FPNN: Field Probing Neural Networks for 3D DataCode0
Volumetric and Multi-View CNNs for Object Classification on 3D DataCode0
Orientation-boosted Voxel Nets for 3D Object Recognition—0
Efficient Global Point Cloud Alignment using Bayesian Nonparametric Mixtures—0
Sparse 3D convolutional neural networksCode0
Analysis by Synthesis: 3D Object Recognition by Object Reconstruction—0
Dual coordinate solvers for large-scale structural SVMs—0
Integration of 3D Object Recognition and Planning for Robotic Manipulation: A Preliminary Report—0
Matching objects across the textured-smooth continuum—0
Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition—0
SLAM++: Simultaneous Localisation and Mapping at the Level of Objects—0
Rotational Projection Statistics for 3D Local Surface Description and Object Recognition—0
3D Object Recognition with Deep Belief Nets—0
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