{"url":"/dataset/fishyscapes","name":"Fishyscapes","full_name":null,"description_markdown":"**Fishyscapes** is a public benchmark for uncertainty estimation in a real-world task of semantic segmentation for urban driving. It evaluates pixel-wise uncertainty estimates towards the detection of anomalous objects in front of the vehicle.","description_withheld":null,"homepage":"https://fishyscapes.com/","introduced_date":"2019-04-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-fishyscapes-benchmark-measuring-blind","title":"The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation","first_author":"Hermann Blum","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"}],"languages":[],"variants":["Fishyscapes","Fishyscapes L&F"],"data_loaders":[{"repo":"https://github.com/hermannsblum/bdl-benchmark","url":"https://colab.research.google.com/github/hermannsblum/bdl-benchmark/blob/master/notebooks/fishyscapes.ipynb","frameworks":["tf"]}],"num_papers_in_archive":51,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/anomaly-detection-on-fishyscapes-l-f","task":"Anomaly Detection","dataset_variant":"Fishyscapes L&F","rows":18,"metrics":["AP","FPR95"],"first_row_in_archive_order":{"model":"cDNP+OE","paper":"/paper/far-away-in-the-deep-space-nearest-neighbor","metrics":{"AP":"69.8","FPR95":"7.5"},"code_links":[{"title":"silviogalesso/dense-ood-knns","url":"https://github.com/silviogalesso/dense-ood-knns"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/anomaly-detection-on-fishyscapes-1","task":"Anomaly Detection","dataset_variant":"Fishyscapes","rows":8,"metrics":["AP","FPR95"],"first_row_in_archive_order":{"model":"RPL+CoroCL","paper":"/paper/residual-pattern-learning-for-pixel-wise-out","metrics":{"AP":"95.96","FPR95":"0.52"},"code_links":[{"title":"yyliu01/rpl","url":"https://github.com/yyliu01/rpl"},{"title":"yyliu01/it2","url":"https://github.com/yyliu01/it2"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/unmasking-anomalies-in-road-scene","title":"Unmasking Anomalies in Road-Scene Segmentation","date":"2023-07-25","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/concurrent-misclassification-and-out-of","title":"Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow","date":"2023-05-16","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/residual-pattern-learning-for-pixel-wise-out","title":"Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation","date":"2022-11-26","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":3,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/far-away-in-the-deep-space-nearest-neighbor","title":"Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detection","date":"2022-11-12","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/densehybrid-hybrid-anomaly-detection-for","title":"DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition","date":"2022-07-06","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":12,"samples_unverified":1,"pointer_only_for_licence":13,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dense-anomaly-detection-by-robust-learning-on","title":"Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data","date":"2021-12-23","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/pixel-wise-energy-biased-abstention-learning","title":"Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes","date":"2021-11-24","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/consensus-synergizes-with-memory-a-simple","title":"Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes","date":"2021-11-24","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/standardized-max-logits-a-simple-yet","title":"Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation","date":"2021-07-23","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/pixel-wise-anomaly-detection-in-complex","title":"Pixel-wise Anomaly Detection in Complex Driving Scenes","date":"2021-03-09","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/simultaneous-semantic-segmentation-and","title":"Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift","date":"2019-08-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/the-fishyscapes-benchmark-measuring-blind","title":"The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation","date":"2019-04-05","rows_on_this_dataset":5,"code_links":1,"syntology":null},{"paper":"/paper/evaluating-bayesian-deep-learning-methods-for","title":"Evaluating Bayesian Deep Learning Methods for Semantic Segmentation","date":"2018-11-30","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":27,"samples_ran":18,"samples_unverified":9,"pointer_only_for_licence":16,"papers_with_no_sample_that_ran":1,"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."}