Neural Plasticity-Inspired Multimodal Foundation Model for Earth
Observation

Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation

22 March 2024

Zhitong Xiong

Adam J. Stewart

Ioannis Papoutsis

Gustau Camps-Valls

Xiao Xiang Zhu

Papers citing "Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation"

6 / 6 papers shown

Title
Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation Thomas Kerdreux A. Tuel Quentin Febvre A. Mouche Bertrand Chapron 54 0 0 09 Apr 2025
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 87 93 0 30 Dec 2022
EarthNets: Empowering AI in Earth Observation Zhitong Xiong Fahong Zhang Yi Wang Yilei Shi Xiao Xiang Zhu 70 70 0 10 Oct 2022
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 370 2,713 0 28 Jan 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 243 5,353 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 271 4,299 0 29 Apr 2021