SOTAVerified

Cloud Removal

The majority of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, persistent cloud coverage affects the remote sensing practitioner's capabilities of a continuous and seamless monitoring of our planet. Cloud removal is the task of reconstructing cloud-covered information while preserving originally cloud-free details.

Image Source: URL

Papers

Showing 1120 of 56 papers

TitleStatusHype
UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time SeriesCode1
PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite ImageryCode1
Multi-Modal and Multi-Resolution Data Fusion for High-Resolution Cloud Removal: A Novel Baseline and BenchmarkCode1
GLF-CR: SAR-Enhanced Cloud Removal with Global-Local FusionCode1
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud RemovalCode1
SSSNET: Semi-Supervised Signed Network ClusteringCode1
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention NetworksCode1
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical ModelCode1
Seeing Through Clouds in Satellite ImagesCode1
Cloud removal in remote sensing images using generative adversarial networks and SAR-to-optical image translationCode1
Show:102550
← PrevPage 2 of 6Next →

No leaderboard results yet.