UniverSat is a ViT-style model with a universal patch encoder enabling self-supervised training on heterogeneous multimodal Earth observation data from varying resolutions and sensors.
Zooming out on zooming in: Advancing super-resolution for remote sensing.arXiv:2311.18082, 2023
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UNVERDICTED 4representative citing papers
GeoSR-Bench is the first SR benchmark that directly measures how super-resolved remote sensing imagery improves performance on land cover segmentation, infrastructure mapping, and biophysical variable estimation rather than relying on fidelity metrics.
Flow matching achieves single-step pixel accuracy and 20-step perceptual quality for Sentinel-2 super-resolution, outperforming diffusion and Real-ESRGAN while enabling large-scale 2.5 m land-cover products.
SatFusion unifies multi-frame super-resolution and pansharpening by extracting semantic features from multiple LR multispectral frames and adding structural details from an HR panchromatic image, with an advanced panchromatic-guided variant.
citing papers explorer
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UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation
UniverSat is a ViT-style model with a universal patch encoder enabling self-supervised training on heterogeneous multimodal Earth observation data from varying resolutions and sensors.
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Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
GeoSR-Bench is the first SR benchmark that directly measures how super-resolved remote sensing imagery improves performance on land cover segmentation, infrastructure mapping, and biophysical variable estimation rather than relying on fidelity metrics.
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Flow matching for Sentinel-2 super-resolution: implementation, application, and implications
Flow matching achieves single-step pixel accuracy and 20-step perceptual quality for Sentinel-2 super-resolution, outperforming diffusion and Real-ESRGAN while enabling large-scale 2.5 m land-cover products.
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SatFusion: A Unified Framework for Enhancing Remote Sensing Images via Multi-Frame and Multi-Source Images Fusion
SatFusion unifies multi-frame super-resolution and pansharpening by extracting semantic features from multiple LR multispectral frames and adding structural details from an HR panchromatic image, with an advanced panchromatic-guided variant.