{"url":"/dataset/indoor-6","name":"Indoor-6","full_name":null,"description_markdown":"The Indoor-6 dataset was created from multiple sessions captured in six indoor scenes over multiple days. The pseudo ground truth (pGT) 3D point clouds and camera poses for each scene are computed using COLMAP. All training data uses only colmap reconstruction from training images. Compared to 7-scenes, the scenes in Indoor-6 are larger, have multiple rooms, contains illumination variations as the images span multiple days and different times of day.","description_withheld":null,"homepage":"https://github.com/microsoft/SceneLandmarkLocalization/tree/3dv24","introduced_date":"2022-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-to-detect-scene-landmarks-for-camera","title":"Learning To Detect Scene Landmarks for Camera Localization","first_author":"Tien Do","url":null},"license":{"name":"CC-BY-4.0","url":"https://github.com/microsoft/SceneLandmarkLocalization/blob/3dv24/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Visual Localization","url":"/task/visual-localization","datasets_with_task":"/datasets/task/visual-localization"},{"name":"Indoor Localization","url":"/task/indoor-localization","datasets_with_task":"/datasets/task/indoor-localization"}],"languages":[],"variants":["Indoor-6"],"data_loaders":[],"num_papers_in_archive":3,"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."}