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. 1707.02392
  4. Cited By
Learning Representations and Generative Models for 3D Point Clouds

Learning Representations and Generative Models for 3D Point Clouds

8 July 2017
Panos Achlioptas
Olga Diamanti
Ioannis Mitliagkas
Leonidas J. Guibas
    3DV
    3DPC
ArXivPDFHTML

Papers citing "Learning Representations and Generative Models for 3D Point Clouds"

15 / 15 papers shown
Title
Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
Ayumu Saito
Prachi Kudeshia
Jiju Poovvancheri
3DPC
33
7
0
25 Apr 2024
H4D: Human 4D Modeling by Learning Neural Compositional Representation
H4D: Human 4D Modeling by Learning Neural Compositional Representation
Boyan Jiang
Yinda Zhang
Xingkui Wei
Xiangyang Xue
Yanwei Fu
3DH
19
19
0
02 Mar 2022
Learning Compositional Representation for 4D Captures with Neural ODE
Learning Compositional Representation for 4D Captures with Neural ODE
Boyan Jiang
Yinda Zhang
Xingkui Wei
Xiangyang Xue
Yanwei Fu
11
28
0
15 Mar 2021
Conditional Generative Modeling via Learning the Latent Space
Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe
Kanchana Ranasinghe
Salman Khan
Nick Barnes
Stephen Gould
BDL
21
9
0
07 Oct 2020
Label-Efficient Learning on Point Clouds using Approximate Convex
  Decompositions
Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions
Matheus Gadelha
Aruni RoyChowdhury
Gopal Sharma
E. Kalogerakis
Liangliang Cao
Erik Learned-Miller
Rui Wang
Subhransu Maji
3DPC
11
45
0
30 Mar 2020
PointHop: An Explainable Machine Learning Method for Point Cloud
  Classification
PointHop: An Explainable Machine Learning Method for Point Cloud Classification
Min Zhang
Haoxuan You
Pranav Kadam
Shan Liu
C.-C. Jay Kuo
3DPC
9
109
0
30 Jul 2019
Deep Unsupervised Learning of 3D Point Clouds via Graph Topology
  Inference and Filtering
Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
Siheng Chen
Chaojing Duan
Yaoqing Yang
Duanshun Li
Chen Feng
Dong Tian
3DPC
27
71
0
11 May 2019
RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for
  Real-Time Point Cloud Shape Completion
RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion
M. Sarmad
H. J. Lee
Y. Kim
3DPC
10
180
0
28 Apr 2019
Points2Pix: 3D Point-Cloud to Image Translation using conditional
  Generative Adversarial Networks
Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks
Stefan Milz
Martin Simon
Kai Fischer
Maximilian Pöpperl
3DPC
16
11
0
26 Jan 2019
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
Despoina Paschalidou
Ali O. Ulusoy
Carolin Schmitt
Luc van Gool
Andreas Geiger
3DV
11
91
0
06 Jan 2019
MVPNet: Multi-View Point Regression Networks for 3D Object
  Reconstruction from A Single Image
MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image
Jinglu Wang
Bo Sun
Yan Lu
3DPC
3DV
14
41
0
23 Nov 2018
Robustness of Conditional GANs to Noisy Labels
Robustness of Conditional GANs to Noisy Labels
Kerry J. Halupka
A. Khetan
Zinan Lin
Stephen Moore
NoLa
16
79
0
08 Nov 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
15
195
0
12 Oct 2018
Clustering-driven Deep Embedding with Pairwise Constraints
Clustering-driven Deep Embedding with Pairwise Constraints
Sharon Fogel
Hadar Averbuch-Elor
Jacob Goldberger
Daniel Cohen-Or
3DPC
11
48
0
22 Mar 2018
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
164
1,940
0
24 Oct 2016
1