{"url":"/dataset/mcubes-p","name":"MCubeS (P)","full_name":"Multimodal Material Segmentation Dataset","description_markdown":"Multimodal material segmentation (MCubeS) dataset contains 500 sets of images from 42 street scenes. Each scene has images for four modalities: RGB, angle of linear polarization (AoLP), degree of linear polarization (DoLP), and near-infrared (NIR). The dataset provides annotated ground truth labels for both material and semantic segmentation for every pixel. The dataset is divided training set with 302 image sets, validation set with 96 image sets, and test set with 102 image sets. Each image has  1224 x 1024 pixels and a total of 20 class labels per pixel.","description_withheld":null,"homepage":"https://github.com/kyotovision-public/multimodal-material-segmentation","introduced_date":"2022-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/multimodal-material-segmentation","title":"Multimodal Material Segmentation","first_author":"Yupeng Liang","url":null},"license":{"name":"MiT","url":"https://github.com/kyotovision-public/multimodal-material-segmentation/blob/main/LICENSE"},"modalities":[],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["MCubeS (P)"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-mcubes-p","task":"Semantic Segmentation","dataset_variant":"MCubeS (P)","rows":8,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"MMSFormer (RGB-A-D)","paper":"/paper/multimodal-transformer-for-material","metrics":{"mIoU":"52.03"},"code_links":[{"title":"csiplab/mmsformer","url":"https://github.com/csiplab/mmsformer"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/sharecmp-polarization-aware-rgb-p-semantic","title":"ShareCMP: Polarization-Aware RGB-P Semantic Segmentation","date":"2023-12-06","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multimodal-transformer-for-material","title":"MMSFormer: Multimodal Transformer for Material and Semantic Segmentation","date":"2023-09-07","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/delivering-arbitrary-modal-semantic","title":"Delivering Arbitrary-Modal Semantic Segmentation","date":"2023-03-02","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":6,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":10,"samples_ran":9,"samples_unverified":1,"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."}