{"url":"/dataset/geojepad","name":"GeoJEPAD","full_name":"GeoJEPA Dataset","description_markdown":"GeoJEPAD is a multimodal dataset combining OpenStreetMap (OSM) data (attributes and geometries) with high-resolution aerial imagery from diverse urban areas.

\r\nSourced from NAIP and OSM and then processed, tiled, and cropped. Geometries and relations represented as graphs with optional visibility edges.\r\n\r\nMotivation:\r\n\r\nCreated to reduce biases introduced by traditional augmentation and sampling techniques, the dataset supports unbiased self-supervised multimodal geospatial learning.\r\n\r\nPotential Use Cases:\t\r\n- Self-supervised multimodal representation learning.\r\n- Semantic segmentation of aerial imagery.\r\n- Geospatial retrieval and urban analytics tasks.\r\n- Benchmarking multimodal fusion models like JEPA.","description_withheld":null,"homepage":"https://github.com/theolundqvist/geojepa","introduced_date":"2025-02-25","introduced_date_note":null,"introduced_by":{"paper":"/paper/geojepa-towards-eliminating-augmentation-and","title":"GeoJEPA: Towards Eliminating Augmentation- and Sampling Bias in Multimodal Geospatial Learning","first_author":"Theodor Lundqvist","url":null},"license":{"name":"Apache 2.0","url":"https://github.com/theolundqvist/geojepa/blob/master/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Self-Supervised Learning","url":"/task/self-supervised-learning","datasets_with_task":"/datasets/task/self-supervised-learning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GeoJEPAD"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}