{"url":"/dataset/structured3d","name":"Structured3D","full_name":null,"description_markdown":"**Structured3D** is a large-scale photo-realistic dataset containing 3.5K house designs (a) created by professional designers with a variety of ground truth 3D structure annotations (b) and generate photo-realistic 2D images (c).\r\nThe dataset consists of rendering images and corresponding ground truth annotations (e.g., semantic, albedo, depth, surface normal, layout) under different lighting and furniture configurations.\r\n\r\nSource: [https://github.com/bertjiazheng/Structured3D](https://github.com/bertjiazheng/Structured3D)\r\nImage Source: [https://github.com/bertjiazheng/Structured3D](https://github.com/bertjiazheng/Structured3D)","description_withheld":null,"homepage":"https://github.com/bertjiazheng/Structured3D","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/structured3d-a-large-photo-realistic-dataset","title":"Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling","first_author":"Jia Zheng","url":null},"license":{"name":"Custom","url":"https://github.com/bertjiazheng/Structured3D#license"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"Metric Learning","url":"/task/metric-learning","datasets_with_task":"/datasets/task/metric-learning"},{"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"},{"name":"Indoor Localization (3-DoF Pose: X, Y, Yaw)","url":"/task/indoor-localization-3-dof-pose-x-y-yaw","datasets_with_task":"/datasets/task/indoor-localization-3-dof-pose-x-y-yaw"},{"name":"Indoor Localization (6-DoF Pose)","url":"/task/indoor-localization-6-dof-pose","datasets_with_task":"/datasets/task/indoor-localization-6-dof-pose"},{"name":"Room Layout Estimation","url":"/task/room-layout-estimation","datasets_with_task":"/datasets/task/room-layout-estimation"},{"name":"Indoor Localization (6D)","url":"/task/indoor-localization-6d","datasets_with_task":"/datasets/task/indoor-localization-6d"},{"name":"2D Indoor Localization (Position + Orientation)","url":"/task/2d-indoor-localization-position-orientation","datasets_with_task":"/datasets/task/2d-indoor-localization-position-orientation"},{"name":"6D Indoor Localization","url":"/task/6d-indoor-localization","datasets_with_task":"/datasets/task/6d-indoor-localization"},{"name":"Indoor Localization (6 DoF Pose)","url":"/task/indoor-localization-6-dof-pose-1","datasets_with_task":"/datasets/task/indoor-localization-6-dof-pose-1"}],"languages":[],"variants":["Structured3D","Structured3D (perspective, furnished)","Structured3D (perspective, emtpy)"],"data_loaders":[{"repo":"https://github.com/Pointcept/Pointcept","url":"https://github.com/Pointcept/Pointcept","frameworks":["pytorch"]},{"repo":"https://github.com/bertjiazheng/Structured3D","url":"https://github.com/bertjiazheng/Structured3D","frameworks":[]},{"repo":"https://github.com/fraunhoferhhi/spvloc","url":"https://github.com/fraunhoferhhi/spvloc","frameworks":["pytorch"]}],"num_papers_in_archive":85,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-structured3d","task":"Semantic Segmentation","dataset_variant":"Structured3D","rows":4,"metrics":["Test mIoU","Validation mIoU"],"first_row_in_archive_order":{"model":"SFSS-MMSI (RGB+Depth+Normal)","paper":"/paper/single-frame-semantic-segmentation-using","metrics":{"Test mIoU":"71.97","Validation mIoU":"75.86"},"code_links":[{"title":"sguttikon/SFSS-MMSI","url":"https://github.com/sguttikon/SFSS-MMSI"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-3-dof-pose-x-y-yaw-on","task":"Indoor Localization (3-DoF Pose: X, Y, Yaw)","dataset_variant":"Structured3D (perspective, emtpy)","rows":1,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":{"model":"SPVLoc","paper":"/paper/spvloc-semantic-panoramic-viewport-matching","metrics":{"<1m median rotation error (deg)":"1.14","<1m median translation error (cm)":"11.7","Recall 10cm (%)":"35.99","Recall 1m (%)":"86.73","Recall 1m 30 deg (%)":"86.25","Recall 50cm (%)":"84.06"},"code_links":[{"title":"fraunhoferhhi/spvloc","url":"https://github.com/fraunhoferhhi/spvloc"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-3-dof-pose-x-y-yaw-on-1","task":"Indoor Localization (3-DoF Pose: X, Y, Yaw)","dataset_variant":"Structured3D (perspective, furnished)","rows":1,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":{"model":"SPVLoc","paper":"/paper/spvloc-semantic-panoramic-viewport-matching","metrics":{"<1m median rotation error (deg)":"1.26","<1m median translation error (cm)":"12.86","Recall 10cm (%)":"30.55","Recall 1m (%)":"84.5","Recall 1m 30 deg (%)":"84.2","Recall 50cm (%)":"81.58"},"code_links":[{"title":"fraunhoferhhi/spvloc","url":"https://github.com/fraunhoferhhi/spvloc"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-6-dof-pose-on","task":"Indoor Localization (6-DoF Pose)","dataset_variant":"Structured3D (perspective, emtpy)","rows":1,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":{"model":"SPVLoc","paper":"/paper/spvloc-semantic-panoramic-viewport-matching","metrics":{"<1m median rotation error (deg)":"1.5","<1m median translation error (cm)":"13.09","Recall 10cm (%)":"28.77","Recall 1m (%)":"86.73","Recall 1m 30 deg (%)":"86.21","Recall 50cm (%)":"83.97"},"code_links":[{"title":"fraunhoferhhi/spvloc","url":"https://github.com/fraunhoferhhi/spvloc"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-6-dof-pose-on-2","task":"Indoor Localization (6-DoF Pose)","dataset_variant":"Structured3D (perspective, furnished)","rows":1,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":{"model":"SPVLoc","paper":"/paper/spvloc-semantic-panoramic-viewport-matching","metrics":{"<1m median rotation error (deg)":"1.62","<1m median translation error (cm)":"14.3","Recall 10cm (%)":"23.54","Recall 1m (%)":"84.5","Recall 1m 30 deg (%)":"84.18","Recall 50cm (%)":"81.48"},"code_links":[{"title":"fraunhoferhhi/spvloc","url":"https://github.com/fraunhoferhhi/spvloc"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-on-structured3d-1","task":"Indoor Localization","dataset_variant":"Structured3D (perspective, furnished)","rows":0,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":null,"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/indoor-localization-on-structured3d-2","task":"Indoor Localization","dataset_variant":"Structured3D (perspective, emtpy)","rows":0,"metrics":["<1m median rotation error (deg)","<1m median translation error (cm)","Recall 10cm (%)","Recall 1m (%)","Recall 1m 30 deg (%)","Recall 50cm (%)"],"first_row_in_archive_order":null,"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/spvloc-semantic-panoramic-viewport-matching","title":"SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments","date":"2024-04-16","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/single-frame-semantic-segmentation-using","title":"Single Frame Semantic Segmentation Using Multi-Modal Spherical Images","date":"2023-08-18","rows_on_this_dataset":4,"code_links":1,"syntology":null}],"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."}