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Gaussian Point Cloud Autoencoder for Partial Point Cloud Reconstruction

https://doi.org/10.2139/ssrn.4728672
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inferredcites →https://doi.org/10.1007/978-3-030-58545-7_21openalex-extracted
GRNet: Gridding Residual Network for Dense Point Cloud Completion
inferredcites →https://doi.org/10.1007/978-3-030-58595-2_31openalex-extracted
Detail Preserved Point Cloud Completion via Separated Feature Aggregation
inferredcites →https://doi.org/10.1007/978-3-319-46466-4_29openalex-extracted
Learning a Predictable and Generative Vector Representation for Objects
inferredcites →https://doi.org/10.1016/j.asoc.2017.08.032openalex-extracted
Two improved k-means algorithms
inferredcites →https://doi.org/10.1016/j.cag.2020.12.004openalex-extracted
Single-View 3D reconstruction: A Survey of deep learning methods
inferredcites →https://doi.org/10.1016/j.cviu.2014.04.011openalex-extracted
SHOT: Unique signatures of histograms for surface and texture description
inferredcites →https://doi.org/10.1016/j.neucom.2019.12.032openalex-extracted
Point Encoder GAN: A deep learning model for 3D point cloud inpainting
inferredcites →https://doi.org/10.1016/j.spl.2017.02.021openalex-extracted
The multiset EM algorithm
inferredcites →https://doi.org/10.1109/3dv.2018.00088openalex-extracted
PCN: Point Completion Network
inferredcites →https://doi.org/10.1109/cvpr.2016.609openalex-extracted
Volumetric and Multi-view CNNs for Object Classification on 3D Data
inferredcites →https://doi.org/10.1109/cvpr.2017.16openalex-extracted
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.264openalex-extracted
A Point Set Generation Network for 3D Object Reconstruction from a Single Image
inferredcites →https://doi.org/10.1109/cvpr.2017.693openalex-extracted
Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis
inferredcites →https://doi.org/10.1109/cvpr.2018.00029openalex-extracted
FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation
inferredcites →https://doi.org/10.1109/cvpr.2018.00295openalex-extracted
PU-Net: Point Cloud Upsampling Network
inferredcites →https://doi.org/10.1109/cvpr.2019.00110openalex-extracted
3D Point Capsule Networks
inferredcites →https://doi.org/10.1109/cvpr.2019.00352openalex-extracted
What Do Single-View 3D Reconstruction Networks Learn?
inferredcites →https://doi.org/10.1109/cvpr41558.2019openalex-extracted
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00087openalex-extracted
Cascaded Refinement Network for Point Cloud Completion
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00201openalex-extracted
Point Cloud Completion by Skip-Attention Network With Hierarchical Folding
inferredcites →https://doi.org/10.1109/iccv.2017.230openalex-extracted
Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs
inferredcites →https://doi.org/10.1109/iccv.2019.00730openalex-extracted
PU-GAN: A Point Cloud Upsampling Adversarial Network
inferredcites →https://doi.org/10.1109/iros.2015.7353481openalex-extracted
VoxNet: A 3D Convolutional Neural Network for real-time object recognition
inferredcites →https://doi.org/10.1109/robot.2009.5152473openalex-extracted
Fast Point Feature Histograms (FPFH) for 3D registration
inferredcites →https://doi.org/10.1109/tvcg.2019.2896310openalex-extracted
VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes
inferredcites →https://doi.org/10.1145/3072959.3073608openalex-extracted
O-CNN
inferredcites →https://doi.org/10.1145/3326362openalex-extracted
Dynamic Graph CNN for Learning on Point Clouds
inferredcites →https://doi.org/10.1177/0278364913491297openalex-extracted
Vision meets robotics: The KITTI dataset
inferredcites →https://doi.org/10.1609/aaai.v34i07.6827openalex-extracted
Morphing and Sampling Network for Dense Point Cloud Completion
inferredcites →https://doi.org/10.48550/arxiv.1512.03012openalex-extracted
ShapeNet: An Information-Rich 3D Model Repository
inferredcites →https://doi.org/10.48550/arxiv.1610.07584openalex-extracted
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
inferredcites →https://doi.org/10.48550/arxiv.1612.00593openalex-extracted
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1706.02413openalex-extracted
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
inferredcites →https://doi.org/10.48550/arxiv.1707.02392openalex-extracted
Learning Representations and Generative Models for 3D Point Clouds
inferredcites →https://doi.org/10.48550/arxiv.1708.03498openalex-extracted
Neural Expectation Maximization
inferredcites →https://doi.org/10.48550/arxiv.1708.05375openalex-extracted
Learning a Multi-View Stereo Machine
inferredcites →https://doi.org/10.48550/arxiv.1805.09957openalex-extracted
Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions
inferredcites →https://doi.org/10.48550/arxiv.1811.00974openalex-extracted
Neural Likelihoods via Cumulative Distribution Functions
inferredcites →https://doi.org/10.48550/arxiv.1902.05522openalex-extracted
Superposition of many models into one
inferredcites →https://doi.org/10.48550/arxiv.2002.06715openalex-extracted
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning
inferredcites →https://doi.org/10.48550/arxiv.2103.03230openalex-extracted
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
inferredcites →https://doi.org/10.6084/m9.figshare.5813382openalex-extracted
Neural Expectation Maximization
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