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Point Cloud Generation

15 papers with code · Computer Vision

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Energy-Based Processes for Exchangeable Data

ICML 2020 google-research/google-research

Recently there has been growing interest in modeling sets with exchangeability such as point clouds.

DENOISING POINT CLOUD GENERATION

PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

ICCV 2019 stevenygd/PointFlow

Specifically, we learn a two-level hierarchy of distributions where the first level is the distribution of shapes and the second level is the distribution of points given a shape.

POINT CLOUD GENERATION VARIATIONAL INFERENCE

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction

21 Jun 2017chenhsuanlin/3D-point-cloud-generation

Conventional methods of 3D object generative modeling learn volumetric predictions using deep networks with 3D convolutional operations, which are direct analogies to classical 2D ones.

3D OBJECT RECONSTRUCTION POINT CLOUD GENERATION

3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions

ICCV 2019 seowok/TreeGAN

In this paper, we propose a novel generative adversarial network (GAN) for 3D point clouds generation, which is called tree-GAN.

POINT CLOUD GENERATION

Learning Gradient Fields for Shape Generation

ECCV 2020 RuojinCai/ShapeGF

Point cloud generation thus amounts to moving randomly sampled points to high-density areas.

POINT CLOUD GENERATION

Deep Generative Modeling of LiDAR Data

4 Dec 2018pclucas14/lidar_generation

In this work, we show that one can adapt deep generative models for this task by unravelling lidar scans into a 2D point map.

POINT CLOUD GENERATION

Learning Localized Generative Models for 3D Point Clouds via Graph Convolution

ICLR 2019 diegovalsesia/GraphCNN-GAN

We also study the problem of defining an upsampling layer in the graph-convolutional generator, such that it learns to exploit a self-similarity prior on the data distribution to sample more effectively.

POINT CLOUD GENERATION

Adversarial Autoencoders for Compact Representations of 3D Point Clouds

19 Nov 2018MaciejZamorski/3d-AAE

Deep generative architectures provide a way to model not only images but also complex, 3-dimensional objects, such as point clouds.

3D OBJECT RETRIEVAL GENERATING 3D POINT CLOUDS POINT CLOUD GENERATION REPRESENTATION LEARNING

SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds

NeurIPS 2020 ANLGBOY/SoftFlow

Flow-based generative models are composed of invertible transformations between two random variables of the same dimension.

POINT CLOUD GENERATION

Discrete Point Flow Networks for Efficient Point Cloud Generation

ECCV 2020 Regenerator/dpf-nets

Generative models have proven effective at modeling 3D shapes and their statistical variations.

3D SHAPE REPRESENTATION POINT CLOUD GENERATION