{"url":"/dataset/transproteus","name":"TransProteus","full_name":null,"description_markdown":"The dataset contains procedurally generated images of transparent vessels containing liquid and objects . The data for each image includes segmentation maps, 3d depth maps, and normal maps of of the liquid or object inside the transparent vessel, and the vessel. In addition, the properties of the materials inside the containers are given(color/transparency/roughness/metalness). \r\nIn addition, a natural image benchmark for the 3d/depth estimation of objects inside transparent containers is supplied.\r\n3d models of the objects (GTLF) are also supplied.","description_withheld":null,"homepage":"https://www.cs.toronto.edu/matterlab/TransProteus/","introduced_date":"2021-12-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/predicting-3d-shapes-masks-and-properties-of","title":"Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset","first_author":"Sagi Eppel","url":null},"license":{"name":"MIT License","url":"https://github.com/sagieppel/Predicting-3D-shape-of-liquid-and-objects-inside-transparent-vessels-as-XYZ-map-from-a-single-image/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3d meshes","url":"/datasets/modality/3d-meshes"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Single-View 3D Reconstruction","url":"/task/single-view-3d-reconstruction","datasets_with_task":"/datasets/task/single-view-3d-reconstruction"},{"name":"Surface Normals Estimation","url":"/task/surface-normals-estimation","datasets_with_task":"/datasets/task/surface-normals-estimation"},{"name":"Transparent Object Depth Estimation","url":"/task/transparent-object-depth-estimation","datasets_with_task":"/datasets/task/transparent-object-depth-estimation"},{"name":"Material Recognition","url":"/task/material-recognition","datasets_with_task":"/datasets/task/material-recognition"},{"name":"Transparent Object Detection","url":"/task/transparent-object-detection","datasets_with_task":"/datasets/task/transparent-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["TransProteus"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/single-view-3d-reconstruction-on-transproteus","task":"Single-View 3D Reconstruction","dataset_variant":"TransProteus","rows":1,"metrics":["R2"],"first_row_in_archive_order":{"model":"XYZNet","paper":"/paper/predicting-3d-shapes-masks-and-properties-of","metrics":{"R2":"0.94"},"code_links":[{"title":"sagieppel/Predicting-3D-shape-of-liquid-and-objects-inside-transparent-vessels-as-XYZ-map-from-a-single-image","url":"https://github.com/sagieppel/Predicting-3D-shape-of-liquid-and-objects-inside-transparent-vessels-as-XYZ-map-from-a-single-image"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/predicting-3d-shapes-masks-and-properties-of","title":"Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset","date":"2021-09-15","rows_on_this_dataset":1,"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."}