The remarkable achievements of ChatGPT and Generative Pre-trained Transformer 4 (GPT-
4) have sparked a wave of interest and research in the field of large language models …

Onboard information fusion for multisatellites, which is based on spatial computing mode,
can improve the satellites' capability, such as the spatial–temporal coverage, detection …

In this article, we introduce the task of visual grounding for remote sensing data (RSVG).
RSVG aims to localize the referred objects in remote sensing (RS) images with the guidance …

The emergence of large-scale large language models, with GPT-4 as a prominent example,
has significantly propelled the rapid advancement of artificial general intelligence and …

Current state-of-the-art remote sensing salient object detectors always require high-
resolution spatial context to ensure excellent performance, which incurs enormous …

Vision-and-language pretraining (VLP) models have experienced a surge in popularity
recently. By fine-tuning them on specific datasets, significant performance improvements …

Earth observation (EO) is a prime instrument for monitoring land and ocean processes,
studying the dynamics at work, and taking the pulse of our planet. This article gives a bird's …

For visual question answering on remote sensing (RSVQA), current methods scarcely
consider geospatial objects typically with large-scale differences and positional sensitive …

Using high-fidelity image compression makes it possible to transmit remote-sensing images
in real-time. Nevertheless, existing lossy remote-sensing image compression (RSIC) …

The multimodal task of Visual Question Answering (VQA) encompassing elements of
Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers …