With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …

Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …

As remote sensing (RS) data obtained from different sensors become available largely and
openly, multimodal data processing and analysis techniques have been garnering …

Abstract Generative Adversarial Networks (GANs) are one of the most creative advances in
Deep Learning (DL) in recent years. The Remote Sensing (RS) community has adopted …

The majority of optical observations acquired via spaceborne Earth imagery are affected by
clouds. While there is numerous prior work on reconstructing cloud-covered information …

The challenge of the cloud removal task can be alleviated with the aid of Synthetic Aperture
Radar (SAR) images that can penetrate cloud cover. However, the large domain gap …

The existence of clouds affects the quality of optical remote sensing images. Cloud removal
is an important preprocessing procedure to effectively improve the utilization of optical …

Dense time series of optical satellite imagery describing vegetation activity provide essential
information for the efficient and regular monitoring of vegetation. Nevertheless, the temporal …

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth
observation. Clouds in optical remote sensing images seriously affect the visibility of the …

Clouds and haze often occlude optical satellite images, hindering continuous, dense
monitoring of the Earth's surface. Although modern deep learning methods can implicitly …