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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
SUGAR: Pre-training 3D Visual Representations for Robotics—0
TANDEM3D: Active Tactile Exploration for 3D Object Recognition—0
Towards Robust 3D Object Recognition with Dense-to-Sparse Deep Domain Adaptation—0
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding—0
Variable-Viewpoint Representations for 3D Object Recognition—0
Volumetric Convolution: Automatic Representation Learning in Unit Ball—0
Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images—0
FusionNet: 3D Object Classification Using Multiple Data Representations—0
Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition—0
InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation—0
Integration of 3D Object Recognition and Planning for Robotic Manipulation: A Preliminary Report—0
Interactive Open-Ended Learning for 3D Object Recognition—0
Investigating the Importance of Shape Features, Color Constancy, Color Spaces and Similarity Measures in Open-Ended 3D Object Recognition—0
L3DOC: Lifelong 3D Object Classification—0
Learning Relationships for Multi-View 3D Object Recognition—0
Lifelong Ensemble Learning based on Multiple Representations for Few-Shot Object Recognition—0
LM-MCVT: A Lightweight Multi-modal Multi-view Convolutional-Vision Transformer Approach for 3D Object Recognition—0
Look Further to Recognize Better: Learning Shared Topics and Category-Specific Dictionaries for Open-Ended 3D Object Recognition—0
Matching objects across the textured-smooth continuum—0
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds—0
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects—0
Multi-View Harmonized Bilinear Network for 3D Object Recognition—0
FPNN: Field Probing Neural Networks for 3D DataCode0
MVT: Multi-view Vision Transformer for 3D Object RecognitionCode0
Topology-Guided Knowledge Distillation for Efficient Point Cloud ProcessingCode0
Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled DataCode0
SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point CloudsCode0
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable NetworksCode0
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning ModelsCode0
On Automatic Data Augmentation for 3D Point Cloud ClassificationCode0
One Noise to Rule Them All: Multi-View Adversarial Attacks with Universal PerturbationCode0
Learning a Hierarchical Latent-Variable Model of 3D ShapesCode0
Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled HolesCode0
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingCode0
Volumetric and Multi-View CNNs for Object Classification on 3D DataCode0
Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization NetworksCode0
OrthographicNet: A Deep Transfer Learning Approach for 3D Object Recognition in Open-Ended DomainsCode0
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN ModelsCode0
Triangle-Net: Towards Robustness in Point Cloud LearningCode0
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape RecognitionCode0
R2-MLP: Round-Roll MLP for Multi-View 3D Object RecognitionCode0
Dominant Set Clustering and Pooling for Multi-View 3D Object RecognitionCode0
Triplet-Center Loss for Multi-View 3D Object RetrievalCode0
Targeted View-Invariant Adversarial Perturbations for 3D Object RecognitionCode0
Multi-level 3D CNN for Learning Multi-scale Spatial FeaturesCode0
Task-Aware Monocular Depth Estimation for 3D Object DetectionCode0
Sparse 3D convolutional neural networksCode0
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