Pixel‑Level Foundation Model for Earth Observation Sets New SOTA Across Tasks, Excelling with Sparse Labels
A joint team from Cambridge, Aalto and Bristol introduces TESSERA, a pixel‑level remote‑sensing foundation model that leverages a Barlow‑Twins self‑supervised scheme and a novel d‑pixel data organization to achieve state‑of‑the‑art accuracy on classification, segmentation and regression tasks, especially when annotations are scarce.
