Equivariant Multi-View Networks
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- Type
- preprint
- Published
- 2019-04-01
- Cited by
- 112
- References
- 42
- Access
- Open access
- OpenAlex
- https://openalex.org/W2934307116
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:90260573
Keywords
Equivariant map, Pooling, Invariant (physics), Computer science, Artificial intelligence
References
- Multi-view Convolutional Neural Networks for 3D Shape Recognition
- The Canonical Coordinates Method for Pattern Deformation: Theoretical and Computational Considerations
- ImageNet: A large-scale hierarchical image database
- Canonical Decomposition of Steerable Functions
- ShapeNet: An Information-Rich 3D Model Repository
- Deep Residual Learning for Image Recognition
- VoxNet: A 3D Convolutional Neural Network for real-time object recognition
- Geodesic Convolutional Neural Networks on Riemannian Manifolds
- Group Equivariant Convolutional Networks
- Volumetric and Multi-view CNNs for Object Classification on 3D Data
- RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints
- Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- Harmonic Networks: Deep Translation and Rotation Equivariance
- ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes
- Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
- Deep Aggregation of Local 3D Geometric Features for 3D Model Retrieval
- Matterport3D: Learning from RGB-D Data in Indoor Environments
- Ensemble of PANORAMA-based convolutional neural networks for 3D model classification and retrieval
- Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds
Cited by
- Multiview Aggregation for Learning Category-Specific Shape Reconstruction
- GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs
- Hexagonal Convolutional Neural Networks for Hexagonal Grids
- Affine Self Convolution
- Quaternion Equivariant Capsule Networks for 3D Point Clouds
- Theoretical Aspects of Group Equivariant Neural Networks
- RotEqNet: Rotation-Equivariant Network for Fluid Systems with Symmetric High-Order Tensors
- Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning
- On Learning Sets of Symmetric Elements
- View-GCN: View-Based Graph Convolutional Network for 3D Shape Analysis
- Geometric Prediction: Moving Beyond Scalars
- Boosting deep neural networks with geometrical prior knowledge: a survey
- Global Context Aware Convolutions for 3D Point Cloud Understanding
- Indoor Scene Change Captioning Based on Multimodality Data
- RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval
- Deep Positional and Relational Feature Learning for Rotation-Invariant Point Cloud Analysis
- A Group-Theoretic Framework for Data Augmentation
- MVTN: Multi-View Transformation Network for 3D Shape Recognition
- Learning Equivariant Representations
- RotPredictor: Unsupervised Canonical Viewpoint Learning for Point Cloud Classification