Mesh Variational Autoencoders with Edge Contraction Pooling
Explore this paper's citation graph
- Type
- preprint
- Published
- 2019-08-07
- Cited by
- 40
- References
- 43
- Access
- Open access
- OpenAlex
- https://openalex.org/W2966673793
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:199472548
Keywords
Pooling, Polygon mesh, Computer science, Embedding, Artificial intelligence
References
- Deep Convolutional Networks on Graph-Structured Data
- On Information and Sufficiency
- Auto-Encoding Variational Bayes
- SCAPE: shape completion and animation of people
- Dyna
- A remeshing approach to multiresolution modeling
- Articulated mesh animation from multi-view silhouettes
- Sparse localized deformation components
- Learning Structured Output Representation using Deep Conditional Generative Models
- VoxNet: A 3D Convolutional Neural Network for real-time object recognition
- Surface simplification using quadric error metrics
- Geodesic Convolutional Neural Networks on Riemannian Manifolds
- Anisotropic Diffusion Descriptors
- Learning shape correspondence with anisotropic convolutional neural networks
- Efficient and Flexible Deformation Representation for Data-Driven Surface Modeling
- Data‐Driven Shape Interpolation and Morphing Editing
- Geometric Deep Learning: Going beyond Euclidean data
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- Smooth interpolation of key frames in a Riemannian shell space
- Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
Cited by
- CLOTH3D: Clothed 3D Humans
- A survey on deep geometry learning: From a representation perspective
- Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders
- Learning a shared deformation space for efficient design-preserving garment transfer
- A Revisit of Shape Editing Techniques: From the Geometric to the Neural Viewpoint
- Learning Feature Aggregation for Deep 3D Morphable Models
- Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes
- 3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces
- Variational 3D Mesh Generation of Man-Made Objects
- A Survey of Deep Learning-Based Mesh Processing
- Deep Structural Causal Shape Models
- ImplicitPCA: Implicitly-proxied parametric encoding for collision-aware garment reconstruction
- A digital twin modeling method for array antenna assembly performance real-time analysis
- A survey of deep learning-based 3D shape generation
- What's the Situation With Intelligent Mesh Generation: A Survey and Perspectives
- SpecTrHuMS: Spectral transformer for human mesh sequence learning
- Generative Models for the Deformation of Industrial Shapes with Linear Geometric Constraints: model order and parameter space reductions
- WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
- GeoLatent: A Geometric Approach to Latent Space Design for Deformable Shape Generators
- Construction of Shape Atlas for Abdominal Organs using Three-Dimensional Mesh Variational Autoencoder
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