{"url":"/dataset/mid-intrinsics","name":"MID Intrinsics","full_name":null,"description_markdown":"Intrinsic component extension of MIT Multi-Illumination Dataset proposed in the paper \"Intrinsic Image Decomposition via Ordinal Shading\", [Chris Careaga](https://ccareaga.github.io/) and [Yağız Aksoy](https://yaksoy.github.io), ACM Transactions on Graphics, 2023 \r\n\r\n### [Project Page](https://yaksoy.github.io/MIDIntrinsics/) | [Paper](https://yaksoy.github.io/papers/TOG23-Intrinsic.pdf) | [Video](https://youtu.be/pWtJd3hqL3c) | [Supplementary](https://yaksoy.github.io/papers/TOG23-Intrinsic-Supp.pdf) | [Data](https://1sfu-my.sharepoint.com/:f:/g/personal/ctc32_sfu_ca/EjZMBeiaFehHiRh0pBCNcDoBLA-e4g5prym4zjIfIiRCUA?e=UFNUsZ)\r\n\r\nWe provide estimations of albedo and shading for the [MIT Multi-Illumination Dataset](https://projects.csail.mit.edu/illumination/)","description_withheld":null,"homepage":"https://yaksoy.github.io/MIDIntrinsics/","introduced_date":"2023-10-28","introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY-NC-SA","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Inverse Rendering","url":"/task/inverse-rendering","datasets_with_task":"/datasets/task/inverse-rendering"},{"name":"Intrinsic Image Decomposition","url":"/task/intrinsic-image-decomposition","datasets_with_task":"/datasets/task/intrinsic-image-decomposition"}],"languages":[],"variants":["MID Intrinsics"],"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."}