{"url":"/dataset/isprs-potsdam","name":"ISPRS Potsdam","full_name":"2D Semantic Labeling Contest - Potsdam","description_markdown":"The data set contains 38 patches (of the same size), each consisting of a true orthophoto (TOP) extracted from a larger TOP mosaic.\r\n\r\nSource: [ISPRS](https://www2.isprs.org/commissions/comm2/wg4/benchmark/2d-sem-label-potsdam/)","description_withheld":null,"homepage":"https://www2.isprs.org/commissions/comm2/wg4/benchmark/2d-sem-label-potsdam/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Open Vocabulary Semantic Segmentation","url":"/task/open-vocabulary-semantic-segmentation","datasets_with_task":"/datasets/task/open-vocabulary-semantic-segmentation"}],"languages":[],"variants":["ISPRS Potsdam"],"data_loaders":[{"repo":"https://github.com/fthbng77/Gazebo_SegNet_ImageNet_DephtNet","url":"https://github.com/fthbng77/Gazebo_SegNet_ImageNet_DephtNet","frameworks":["pytorch"]}],"num_papers_in_archive":27,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-isprs-potsdam","task":"Semantic Segmentation","dataset_variant":"ISPRS Potsdam","rows":20,"metrics":["Overall Accuracy","Mean F1","Mean IoU"],"first_row_in_archive_order":{"model":"AerialFormer-B","paper":"/paper/aerialformer-multi-resolution-transformer-for","metrics":{"Mean F1":"94.1","Mean IoU":"89.1","Overall Accuracy":"93.9"},"code_links":[{"title":"UARK-AICV/AerialFormer","url":"https://github.com/UARK-AICV/AerialFormer"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/open-vocabulary-semantic-segmentation-on-16","task":"Open Vocabulary Semantic Segmentation","dataset_variant":"ISPRS Potsdam","rows":1,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"SkySense-O","paper":"/paper/skysense-a-multi-modal-remote-sensing","metrics":{"mIoU":"54.1"},"code_links":[{"title":"jack-bo1220/awesome-remote-sensing-foundation-models","url":"https://github.com/jack-bo1220/awesome-remote-sensing-foundation-models"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/dynamic-dictionary-learning-for-remote","title":"Dynamic Dictionary Learning for Remote Sensing Image Segmentation","date":"2025-03-09","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":9,"samples_unverified":3,"pointer_only_for_licence":12,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/stochastic-subsampling-with-average-pooling","title":"Stochastic Subsampling With Average Pooling","date":"2024-09-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/sfa-net-semantic-feature-adjustment-network","title":"SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation","date":"2024-09-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/u-net-ensemble-for-enhanced-semantic","title":"U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery","date":"2024-06-08","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/lsknet-a-foundation-lightweight-backbone-for","title":"LSKNet: A Foundation Lightweight Backbone for Remote Sensing","date":"2024-03-18","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/skysense-a-multi-modal-remote-sensing","title":"SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery","date":"2023-12-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/aerialformer-multi-resolution-transformer-for","title":"AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation","date":"2023-06-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-billion-scale-foundation-model-for-remote","title":"A Billion-scale Foundation Model for Remote Sensing Images","date":"2023-04-11","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/advancing-plain-vision-transformer-towards","title":"Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model","date":"2022-08-08","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":3,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/semantic-labeling-of-high-resolution-images","title":"Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers","date":"2022-06-20","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/an-empirical-study-of-remote-sensing","title":"An Empirical Study of Remote Sensing Pretraining","date":"2022-04-06","rows_on_this_dataset":4,"code_links":2,"syntology":null},{"paper":"/paper/efficient-hybrid-transformer-learning-global","title":"UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery","date":"2021-09-18","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/transformer-meets-convolution-a-bilateral","title":"Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images","date":"2021-06-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multiattention-network-for-semantic","title":"Multiattention network for semantic segmentation of fine-resolution remote sensing images","date":"2021-05-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/transformer-meets-dcfam-a-novel-semantic","title":"A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images","date":"2021-04-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/abcnet-attentive-bilateral-contextual-network","title":"ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images","date":"2021-02-04","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":20,"samples_ran":16,"samples_unverified":4,"pointer_only_for_licence":16,"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."}