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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
TLDR
We design a novel type of neural network that directly consumes point clouds, which well respects the permutation invariance of points in the input. Expand
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
TLDR
We introduce a hierarchical neural network, named as PointNet++, to process a set of points sampled in a metric space in a hierarchical fashion. Expand
The Earth Mover's Distance as a Metric for Image Retrieval
TLDR
We investigate the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval. Expand
ShapeNet: An Information-Rich 3D Model Repository
TLDR
We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. Expand
A Concise and Provably Informative Multi‐Scale Signature Based on Heat Diffusion
TLDR
We propose a novel point signature based on the properties of the heat diffusion process on a shape. Expand
A metric for distributions with applications to image databases
TLDR
We introduce a new distance between two distributions that we call the Earth Mover's Distance, which reflects the minimal amount of work that must be performed to transform one distribution into the other by moving "distribution mass" around. Expand
Frustum PointNets for 3D Object Detection from RGB-D Data
TLDR
In this work, we study 3D object detection from RGBD data in both indoor and outdoor scenes by popping up RGB-D scans. Expand
A Point Set Generation Network for 3D Object Reconstruction from a Single Image
TLDR
In this paper we address the problem of 3D reconstruction from a single image, generating a straight-forward form of output – point cloud coordinates. Expand
Volumetric and Multi-view CNNs for Object Classification on 3D Data
TLDR
In this paper, we aim to improve both volumetric CNNs and multi-view CNNs according to extensive analysis of existing approaches for object classification on 3D data. Expand
Robust Monte Carlo methods for light transport simulation
TLDR
Light transport algorithms generate realistic images by simulating the emission and scattering of light in an artificial environment. Expand
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