VistaFormer: Simple Vision Transformers for Satellite Image Time Series Segmentation

The dataset includes trained models, training logs, and test results on PASTIS and MTLCC semantic segmentation benchmark datasets. Both benchmark datasets these models are trained on are crop-type classification benchmarks that use time series Sentinel data as inputs. The PASTIS benchmark covers agricultural land plots in France while the MTLCC benchmark covers agricultural land plots in Germany. Code that accompanies these trained weights and records as well as code that can be used to transform benchmark inputs for use by the trained models can be found here: https://github.com/macdonaldezra/VistaFormer