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. 2406.08079
  4. Cited By
A$^{2}$-MAE: A spatial-temporal-spectral unified remote sensing
  pre-training method based on anchor-aware masked autoencoder

A2^{2}2-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder

12 June 2024
Lixian Zhang
Yi Zhao
Runmin Dong
Jinxiao Zhang
Shuai Yuan
Shilei Cao
Mengxuan Chen
Juepeng Zheng
Weijia Li
Wei Liu
Wayne Zhang
Litong Feng
H. Fu
ArXivPDFHTML

Papers citing "A$^{2}$-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder"

4 / 4 papers shown
Title
Towards a Unified Copernicus Foundation Model for Earth Vision
Towards a Unified Copernicus Foundation Model for Earth Vision
Yi Wang
Zhitong Xiong
Chenying Liu
Adam J. Stewart
Thomas Dujardin
...
Angelos Zavras
Franziska Gerken
Ioannis Papoutsis
Laura Leal-Taixé
Xiao Xiang Zhu
38
1
0
14 Mar 2025
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial
  Representation Learning
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Colorado Reed
Ritwik Gupta
Shufan Li
S. Brockman
Christopher Funk
Brian Clipp
Kurt Keutzer
Salvatore Candido
M. Uyttendaele
Trevor Darrell
113
165
0
30 Dec 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
258
7,337
0
11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
283
5,723
0
29 Apr 2021
1