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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 1–50 of 97 papers

TitleStatusHype
Lifting Multi-View Detection and Tracking to the Bird's Eye ViewCode2
SceneGraphNet: Neural Message Passing for 3D Indoor Scene AugmentationCode2
Omni3D: A Large Benchmark and Model for 3D Object Detection in the WildCode2
BlenderProcCode2
Explainability-Aware One Point Attack for Point Cloud Neural NetworksCode1
MeshWalker: Deep Mesh Understanding by Random WalksCode1
FSD: Fast Self-Supervised Single RGB-D to Categorical 3D ObjectsCode1
SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point CloudsCode0
Dominant Set Clustering and Pooling for Multi-View 3D Object RecognitionCode0
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN ModelsCode0
Multi-level 3D CNN for Learning Multi-scale Spatial FeaturesCode0
OrthographicNet: A Deep Transfer Learning Approach for 3D Object Recognition in Open-Ended DomainsCode0
FPNN: Field Probing Neural Networks for 3D DataCode0
MVT: Multi-view Vision Transformer for 3D Object RecognitionCode0
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
Targeted View-Invariant Adversarial Perturbations for 3D Object RecognitionCode0
Task-Aware Monocular Depth Estimation for 3D Object DetectionCode0
Topology-Guided Knowledge Distillation for Efficient Point Cloud ProcessingCode0
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingCode0
Triangle-Net: Towards Robustness in Point Cloud LearningCode0
Triplet-Center Loss for Multi-View 3D Object RetrievalCode0
On Automatic Data Augmentation for 3D Point Cloud ClassificationCode0
Volumetric and Multi-View CNNs for Object Classification on 3D DataCode0
One Noise to Rule Them All: Multi-View Adversarial Attacks with Universal PerturbationCode0
Sparse 3D convolutional neural networksCode0
Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization NetworksCode0
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
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning ModelsCode0
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable NetworksCode0
Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled DataCode0
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
MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks—0
Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans—0
Occlusion-aware Text-Image-Point Cloud Pretraining for Open-World 3D Object Recognition—0
Offboard 3D Object Detection from Point Cloud Sequences—0
Orientation-boosted Voxel Nets for 3D Object Recognition—0
Performance Evaluation of 3D Correspondence Grouping Algorithms—0
RendNet: Unified 2D/3D Recognizer With Latent Space Rendering—0
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance—0
Rotational Projection Statistics for 3D Local Surface Description and Object Recognition—0
Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition—0
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