Masked Autoencoders in Computer Vision: A Comprehensive Survey-Reference-Cited by-同舟云学术

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Masked Autoencoders in Computer Vision: A Comprehensive Survey

Published:2023 Issue: Volume:11 Page:113560-113579
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhou Zexian¹^ORCID,Liu Xiaojing¹^ORCID

Affiliation:

1. Department of Computer Technology and Application, Qinghai University, Xining, China

Funder

Qinghai Provincial Department of Science and Technology through the Applied Basic Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10278410.pdf?arnumber=10278410

Reference135 articles.

1. Representation learning with contrastive predictive coding;van den oord;arXiv 1807 03748,2018

2. Learning a Similarity Metric Discriminatively, with Application to Face Verification

3. Distilling the knowledge in a neural network;hinton;ArXiv 1503 02531,2015

4. Exploring target representations for masked autoencoders;liu;arXiv 2209 03917,2022

5. Exploring the role of mean teachers in self-supervised masked auto-encoders;lee;Proc Int Conf Learn Represent (ICLR),2023

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