A General Framework For Incomplete Cross-Modal Retrieval With Missing Labels And Missing Modalities-Reference-Cited by-同舟云学术

A General Framework For Incomplete Cross-Modal Retrieval With Missing Labels And Missing Modalities

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Li Mingyang¹,Huang Shao-Lun¹,Zhang Lin¹

Affiliation:

1. Tsinghua University,Tsinghua-Berkeley Shenzhen Institute (TBSI)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747813.pdf?arnumber=9747813

Reference21 articles.

1. On deep multi-view representation learning;wang;International Conference on Machine Learning,2015

2. An Efficient Approach to Informative Feature Extraction from Multimodal Data

3. Semi-supervised learning by entropy minimization;grandvalet;CAP,2005

4. On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval

5. Collecting image annotations using amazon’s mechanical turk;rashtchian;Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk,2010

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