Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

Zero-shot remote sensing scene classification aims to solve the scene classification problem
on unseen categories and has attracted numerous research attention in the remote sensing …

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

The success of the Segment Anything Model (SAM) demonstrates the significance of data-
centric machine learning. However, due to the difficulties and high costs associated with …

Remote sensing images pose distinct challenges for downstream tasks due to their inherent
complexity. While a considerable amount of research has been dedicated to remote sensing …

Object Classification in Remote Sensing Imagery holds paramount importance for extracting
meaningful insights from complex aerial scenes. Conventional methods encounter …

Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise
information for diverse downstream applications. Recent development of the segment …

Monitoring changes in the Earth's surface is crucial for understanding natural processes and
human impacts, necessitating precise and comprehensive interpretation methodologies …

Remote sensing image change captioning (RSICC) is a novel task that aims to describe the
differences between bitemporal images by natural language. Previous methods ignore a …

Abstract Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in
geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide …