DeepPoint3D: Learning Discriminative Local Descriptors using Deep Metric Learning on 3D Point Clouds.(arxiv 2019)

MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds.(arxiv 2019)

Discrete Rotation Equivariance for Point Cloud Recognition.(ICRA 2019)

Generalizing discrete convolutions for unstructured point clouds.(arxiv 2019)

Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions.(2019 Technical report)

3D Local Features for Direct Pairwise Registration.(CVPR 2019)

Dynamic graph cnn for learning on point clouds.(arxiv 2018)

Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling(CVPR 2018)

Pointwise convolutional neural networks.(CVPR 2018)

PointCNN.(NIPS 2018)

PointSIFT: A SIFT-like network module for 3D point cloud semantic segmentation.(arxiv 2018)

Multiresolution tree networks for 3D point cloud processing.(ECCV 2018)

Fully-convolutional point networks for large-scale point clouds.(ECCV 2018)

PointNet: Deep learning on point sets for 3D classification and segmentation.(CVPR 2017)

PointNet++: Deep hierarchical feature learning on point sets in a metric space.(NIPS 2017)

Point2Sequence: Learning the shape representation of 3D point clouds with an attention-based sequence to sequence network.（AAAI 2019)

Adaptive OCNN: A patch-based deep representation of 3D shapes(TOG 2018)

Escape from cells: deep KdNetworks for the recognition of 3D point cloud models.(ICCV 2017)

OctNet: Learning deep 3D representations at high resolutions.(CVPR 2017)

Shape completion using 3DEncoderPredictor CNNs and shape synthesis.(CVPR 2017)

OctNet: Learning deep 3D representations at high resolutions.(CVPR 2017)

Voxnet: A 3D convolutional neural network for real*time object recognition.(IROS 2015)

3D ShapeNets: A deep representation for volumetric shapes.(CVPR 2015)

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs.(CVPR 2017)

Geodesic convolutional neural networks on Riemannian manifolds.(ICCV 2015)

Spectral networks and locally connected networks on graphs.(ICLR 2014)

Learning to Sample.(CVPR 2019)

Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling.(CVPR 2019)

Ecnet: an edge-aware point set consolidation network.(ECCV 2018)

Data-driven upsampling of point clouds.(arxiv 2018)

Pointgrow: Autoregressively learned point cloud generation with self-attention.(arxiv 2018)

PU-Net: Point Cloud Upsampling Network.(CVPR 2018)

Deep points consolidation.(TOG 2015)

Edge-aware point set resampling.(TOG 2013)

Revealing Scenes by Inverting Structure from Motion Reconstructions.(CVPR 2019)

FoldingNet: Point Cloud Auto-encoder via Deep Grid Deformation.(CVPR 2018)

Learning representations and generative models for 3D point clouds.(ICML 2018)

A point set generation network for 3D object reconstruction from a single image.(CVPR2017)

Point Cloud GAN.(ICLR 2019)

Learning Localized Generative Models for 3D Point Clouds via Graph Convolution.(ICLR 2019)

Learning representations and generative models for 3D point clouds.(ICML 2018)

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling.(NIPS 2016)

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction.(AAAI 2018)

AtlasNet: A papiermache approach to learning 3D surface generation. (CVPR2017)

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning.(CVPR 2019)

JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields(CVPR 2019)

3D-BEVIS: Birds-Eye-View Instance Segmentation.(2019 technical Report)

SGPN: Similarity group proposal network for 3D point cloud instance segmentation. (CVPR 2018) Code

Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction.(CVPR 2019)

MVX-Net: Multimodal VoxelNet for 3D Object Detection.(ICRA 2019)

Frustum PointNets for 3D object detection from RGB-D data.(CVPR 2018)

PointNetLK: Robust & Efficient Point Cloud Registration using PointNet.(CVPR 2019)

The Perfect Match: 3D Point Cloud Matching with Smoothed Densities.(CVPR 2019)

Embodied Question Answering in Photorealistic Environments with Point Cloud Perception.(CVPR 2019)

SDRSAC: Semidefinite*Based Randomized Approach for Robust Point Cloud Registration without Correspondences.(CVPR 2019)

Weighted Point Cloud Augmentation for Neural Network Training Data Class*Imblance.(ISRPS 2019)

Supervised Fitting of Geometric Primitives to 3D Point Clouds.(CVPR 2019 oral)

Revealing Scenes by Inverting Structure from Motion Reconstructions.(CVPR 2019)

DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds.(CVPR 2019 oral)(Unsupervised Learning)

USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds.(arxiv 2019)

PPF-FoldNet: Unsupervised learning of rotation invariant 3D local descriptors(ECCV 2018)