{"url":"/dataset/the-benchmark","name":"The Benchmark","full_name":null,"description_markdown":"**The Benchmark** is a collection of datasets for Monocular Height Estimation. It consists of two datasets: GTAH and AHN.\r\n\r\n**GTAH** (Grand Theft Auto for Height estimation) is a large-scale synthetic dataset which is obtained from the game Grand Theft Auto, under different imaging conditions. GTAH contains 28,627 height maps in total and each with a resolution of 1920×1080. For each height map, there are three corresponding RGB images that are captured under different weather conditions.","description_withheld":null,"homepage":"https://thebenchmarkh.github.io/","introduced_date":"2021-12-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-benchmark-transferable-representation","title":"THE Benchmark: Transferable Representation Learning for Monocular Height Estimation","first_author":"Zhitong Xiong","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["The Benchmark"],"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."}