ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2103.04130
  4. Cited By
Learning to Generate 3D Shapes with Generative Cellular Automata

Learning to Generate 3D Shapes with Generative Cellular Automata

6 March 2021
Dongsu Zhang
Changwoon Choi
Jeonghwan Kim
Y. Kim
ArXivPDFHTML

Papers citing "Learning to Generate 3D Shapes with Generative Cellular Automata"

24 / 24 papers shown
Title
Learning Gradient Fields for Shape Generation
Learning Gradient Fields for Shape Generation
Ruojin Cai
Guandao Yang
Hadar Averbuch-Elor
Jinwei Gu
Serge J. Belongie
Noah Snavely
B. Hariharan
3DPC
104
286
0
14 Aug 2020
Multimodal Shape Completion via Conditional Generative Adversarial
  Networks
Multimodal Shape Completion via Conditional Generative Adversarial Networks
Rundi Wu
Xuelin Chen
Yixin Zhuang
Baoquan Chen
3DPC
77
86
0
17 Mar 2020
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
Guandao Yang
Xun Huang
Jinwei Gu
Ming-Yuan Liu
Serge J. Belongie
Bharath Hariharan
3DPC
99
667
0
28 Jun 2019
3D Point Cloud Generative Adversarial Network Based on Tree Structured
  Graph Convolutions
3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions
Dong Wook Shu
Sung Woo Park
Junseok Kwon
3DPC
79
283
0
15 May 2019
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
Chris Choy
JunYoung Gwak
Silvio Savarese
3DPC
149
1,787
0
18 Apr 2019
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical
  Part-level 3D Object Understanding
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding
Kaichun Mo
Shilin Zhu
Angel X. Chang
L. Yi
Subarna Tripathi
Leonidas Guibas
Hao Su
3DPC
3DV
95
732
0
06 Dec 2018
PointGrow: Autoregressively Learned Point Cloud Generation with
  Self-Attention
PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention
Yongbin Sun
Yue Wang
Ziwei Liu
J. Siegel
Sanjay E. Sarma
3DPC
59
195
0
12 Oct 2018
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
Benjamin Graham
Martin Engelcke
Laurens van der Maaten
3DPC
103
1,515
0
28 Nov 2017
Variational Walkback: Learning a Transition Operator as a Stochastic
  Recurrent Net
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
Anirudh Goyal
Nan Rosemary Ke
Surya Ganguli
Yoshua Bengio
DiffM
121
55
0
07 Nov 2017
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
226
5,008
0
02 Nov 2017
Improved Adversarial Systems for 3D Object Generation and Reconstruction
Improved Adversarial Systems for 3D Object Generation and Reconstruction
Edward James Smith
David Meger
GAN
53
172
0
29 Jul 2017
Learning to Generate Samples from Noise through Infusion Training
Learning to Generate Samples from Noise through Infusion Training
Florian Bordes
S. Honari
Pascal Vincent
GAN
DiffM
61
44
0
20 Mar 2017
Mask R-CNN
Mask R-CNN
Kaiming He
Georgia Gkioxari
Piotr Dollár
Ross B. Girshick
ObjD
352
27,181
0
20 Mar 2017
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas Guibas
3DH
3DPC
3DV
PINN
484
14,309
0
02 Dec 2016
Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis
Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis
Angela Dai
C. Qi
Matthias Nießner
3DV
3DPC
78
606
0
01 Dec 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D
  Generative-Adversarial Modeling
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu
Chengkai Zhang
Tianfan Xue
Bill Freeman
J. Tenenbaum
GAN
308
1,953
0
24 Oct 2016
Revisiting Classifier Two-Sample Tests
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
Maxime Oquab
155
402
0
20 Oct 2016
Conditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN Decoders
Aaron van den Oord
Nal Kalchbrenner
Oriol Vinyals
L. Espeholt
Alex Graves
Koray Kavukcuoglu
VLM
204
2,511
0
16 Jun 2016
ShapeNet: An Information-Rich 3D Model Repository
ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang
Thomas Funkhouser
Leonidas Guibas
Pat Hanrahan
Qi-Xing Huang
...
Shuran Song
Hao Su
Jianxiong Xiao
L. Yi
Feng Yu
3DV
162
5,524
0
09 Dec 2015
How (not) to Train your Generative Model: Scheduled Sampling,
  Likelihood, Adversary?
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary?
Ferenc Huszár
OOD
DiffM
GAN
84
296
0
16 Nov 2015
Scheduled Sampling for Sequence Prediction with Recurrent Neural
  Networks
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio
Oriol Vinyals
Navdeep Jaitly
Noam M. Shazeer
143
2,034
0
09 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
1.8K
77,133
0
18 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
301
6,931
0
12 Mar 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
1