Fus-MAE: A cross-attention-based data fusion approach for Masked Autoencoders in remote sensing

5 January 2024

Papers citing "Fus-MAE: A cross-attention-based data fusion approach for Masked Autoencoders in remote sensing"

6 / 6 papers shown

Title
Unsupervised Time-Series Signal Analysis with Autoencoders and Vision Transformers: A Review of Architectures and Applications Hossein Ahmadi Sajjad Emdadi Mahdimahalleh Arman Farahat Banafsheh Saffari AI4TS 24 1 0 23 Apr 2025
BSS-CFFMA: Cross-Domain Feature Fusion and Multi-Attention Speech Enhancement Network based on Self-Supervised Embedding Alimjan Mattursun Liejun Wang Yinfeng Yu 30 2 0 13 Aug 2024
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data Matthew J Allen Francisco Dorr Joseph A. Gallego-Mejia Laura Martínez-Ferrer Anna Jungbluth Freddie Kalaitzis Raúl Ramos-Pollán 33 3 0 06 Jun 2024
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal Patrick Ebel Yajin Xu M. Schmitt Xiaoxiang Zhu 46 87 0 24 Jan 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,434 0 11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 317 5,775 0 29 Apr 2021