A new unlabeled Sentinel-1/Sentinel-2 pretraining dataset, two multimodal self-supervised objectives, and a Swin-Transformer-plus-CNN hybrid improve calving front delineation on CaFFe to 293 m, with an ensemble reaching 75 m against a 38 m human reference.
Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
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SSL4SAR: Self-Supervised Learning for Glacier Calving Front Extraction from SAR Imagery
A new unlabeled Sentinel-1/Sentinel-2 pretraining dataset, two multimodal self-supervised objectives, and a Swin-Transformer-plus-CNN hybrid improve calving front delineation on CaFFe to 293 m, with an ensemble reaching 75 m against a 38 m human reference.