{"url":"/dataset/nighttime-driving","name":"Nighttime Driving","full_name":null,"description_markdown":"**Nighttime Driving** is a dataset of road scenes consisting of 35,000 images ranging from daytime to twilight time and to nighttime. \r\n\r\nImage source: [http://people.ee.ethz.ch/~daid/NightDriving/#](http://people.ee.ethz.ch/~daid/NightDriving/#)","description_withheld":null,"homepage":"http://people.ee.ethz.ch/~daid/NightDriving/#","introduced_date":"2018-10-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/dark-model-adaptation-semantic-image","title":"Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime","first_author":"Dengxin Dai","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Unsupervised Semantic Segmentation","url":"/task/unsupervised-semantic-segmentation","datasets_with_task":"/datasets/task/unsupervised-semantic-segmentation"}],"languages":[],"variants":["Nighttime Driving"],"data_loaders":[{"repo":"https://github.com/igor-morawski/nod","url":"https://github.com/igor-morawski/nod","frameworks":[]}],"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-nighttime-driving","task":"Semantic Segmentation","dataset_variant":"Nighttime Driving","rows":13,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"TADP","paper":"/paper/text-image-alignment-for-diffusion-based","metrics":{"mIoU":"60.8"},"code_links":[{"title":"damaggu/tadp","url":"https://github.com/damaggu/tadp"},{"title":"nkondapa/RSVC","url":"https://github.com/nkondapa/RSVC"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/unsupervised-semantic-segmentation-on-2","task":"Unsupervised Semantic Segmentation","dataset_variant":"Nighttime Driving","rows":1,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"Segmenter ViT-S/16","paper":"/paper/drive-segment-unsupervised-semantic","metrics":{"mIoU":"18.9"},"code_links":[{"title":"vobecant/DriveAndSegment","url":"https://github.com/vobecant/DriveAndSegment"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/coda-instructive-chain-of-domain-adaptation","title":"CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning","date":"2024-03-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/text-image-alignment-for-diffusion-based","title":"Text-image Alignment for Diffusion-based Perception","date":"2023-09-29","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/refign-align-and-refine-for-adaptation-of","title":"Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions","date":"2022-07-14","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":0,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/drive-segment-unsupervised-semantic","title":"Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation","date":"2022-03-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/zero-shot-domain-adaptation-with-a-physics","title":"Zero-Shot Day-Night Domain Adaptation with a Physics Prior","date":"2021-08-11","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dannet-a-one-stage-domain-adaptation-network","title":"DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation","date":"2021-04-22","rows_on_this_dataset":3,"code_links":1,"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/map-guided-curriculum-domain-adaptation-and","title":"Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation","date":"2020-05-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/see-clearer-at-night-towards-robust-nighttime","title":"See Clearer at Night: Towards Robust Nighttime Semantic Segmentation through Day-Night Image Conversion","date":"2019-08-16","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/semantic-nighttime-image-segmentation-with","title":"Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation","date":"2019-01-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dark-model-adaptation-semantic-image","title":"Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime","date":"2018-10-05","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":16,"samples_ran":7,"samples_unverified":9,"pointer_only_for_licence":2,"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."}