Brain-inspired remote sensing foundation models and open problems: A comprehensive survey
The foundation model (FM) has garnered significant attention for its remarkable transfer
performance in downstream tasks. Typically, it undergoes task-agnostic pretraining on a …
performance in downstream tasks. Typically, it undergoes task-agnostic pretraining on a …
A Review of Deep Learning-Based Methods for Road Extraction from High-Resolution Remote Sensing Images
Road extraction from high-resolution remote sensing images has long been a focal and
challenging research topic in the field of computer vision. Accurate extraction of road …
challenging research topic in the field of computer vision. Accurate extraction of road …
Chatearthnet: A global-scale, high-quality image-text dataset for remote sensing
An in-depth comprehension of global land cover is essential in Earth observation, forming
the foundation for a multitude of applications. Although remote sensing technology has …
the foundation for a multitude of applications. Although remote sensing technology has …
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding
We introduce a new benchmark designed to advance the development of general-purpose,
large-scale vision-language models for remote sensing images. Although several vision …
large-scale vision-language models for remote sensing images. Although several vision …
Towards Vision-Language Geo-Foundation Model: A Survey
Vision-Language Foundation Models (VLFMs) have made remarkable progress on various
multimodal tasks, such as image captioning, image-text retrieval, visual question answering …
multimodal tasks, such as image captioning, image-text retrieval, visual question answering …