{"url":"/dataset/inspacetype","name":"InSpaceType","full_name":"Indoor Space Type Dataset for Monocular Depth Analysis","description_markdown":"High Quality Indoor Monocular Depth Estimation Dataset with focus on performance variation across space type\n\n- 1260 high quality evaluation pairs\n- Detailed inference variance across space types \n- Additional indoor image and depth pairs for training","description_withheld":null,"homepage":"https://github.com/DepthComputation/InSpaceType_Benchmark","introduced_date":"2023-09-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/inspacetype-reconsider-space-type-in-indoor","title":"InSpaceType: Reconsider Space Type in Indoor Monocular Depth Estimation","first_author":"Cho-Ying Wu","url":null},"license":{"name":"MIT","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"Indoor Monocular Depth Estimation","url":"/task/indoor-monocular-depth-estimation","datasets_with_task":"/datasets/task/indoor-monocular-depth-estimation"}],"languages":[],"variants":["InSpaceType"],"data_loaders":[],"num_papers_in_archive":2,"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."}