Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering-Reference-Cited by-同舟云学术

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
Short-container-title:

Author:

Xu Jie¹,Ren Yazhou¹,Tang Huayi¹,Pu Xiaorong¹,Zhu Xiaofeng¹,Zeng Ming²,He Lifang³

Affiliation:

1. University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China,611731

2. Carnegie Mellon University,Department of Electrical Computer Engineering,PA,USA,15213

3. Lehigh Univerisity,Department of Computer Science and Engineering,PA,USA,18015

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

Reference55 articles.

1. VMI-VAE: Variational mutual information maximization framework for vae with discrete and continuous priors;serdega,2020

2. Stochastic backpropagation and approximate inference in deep generative models;rezende;ICML,2014

3. Parameter-free auto-weighted multiple graph learning: a framework for multi-view clustering and semi-supervised classification;nie;IJCAI,2016

4. Multi-view clustering and semi-supervised classification with adaptive neighbours;nie;AAAI,2017

5. On spectral clustering: Analysis and an algorithm;ng;NIPS,2002

Cited by 59 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献