{"url":"/dataset/rdd-2020","name":"RDD-2020","full_name":"Road Damage Dataset 2020","description_markdown":"The Road Damage Dataset 2020 (RDD-2020) Secondly is a large-scale heterogeneous dataset comprising 26620 images collected from multiple countries using smartphones. The images are collected from roads in India, Japan and the Czech Republic.\r\n\r\nSource: [Transfer Learning-based Road Damage Detection for Multiple Countries](https://arxiv.org/abs/2008.13101)","description_withheld":null,"homepage":"https://github.com/sekilab/RoadDamageDetector/","introduced_date":"2020-08-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/transfer-learning-based-road-damage-detection","title":"Transfer Learning-based Road Damage Detection for Multiple Countries","first_author":"Deeksha Arya","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Road Damage Detection","url":"/task/road-damage-detection","datasets_with_task":"/datasets/task/road-damage-detection"}],"languages":[],"variants":["RDD-2020"],"data_loaders":[{"repo":"https://github.com/sekilab/RoadDamageDetector","url":"https://github.com/sekilab/RoadDamageDetector","frameworks":["tf"]}],"num_papers_in_archive":4,"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."}