{"url":"/sota/semi-supervised-semantic-segmentation-on-2d","task":{"name":"Semi-Supervised Semantic Segmentation","url":"/task/semi-supervised-semantic-segmentation","note":null},"dataset":{"name":"2D-3D-S","url":"/dataset/2d-3d-s"},"category":"Computer Vision","categories":["Computer Code","Computer Vision","Medical","Robots"],"category_note":null,"description":"Models that are trained with a small number of labeled examples and a large number of unlabeled examples and whose aim is to learn to segment an image (i.e. assign a class to every pixel).","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["mIoU (0.1% labels)","mIoU (0.2% labels)","mIoU (1% labels)"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"mIoU (0.1% labels)":null,"mIoU (0.2% labels)":null,"mIoU (1% labels)":null}},"counts":{"rows":1,"rows_with_code":1,"rows_with_paper_page":1,"rows_dated":1,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"M3L (Linear Fusion B2)","metrics":{"mIoU (0.1% labels)":"40.05","mIoU (0.2% labels)":"44.62","mIoU (1% labels)":"49.28"},"uses_additional_data":false,"paper_date":"2023-04-21","paper":"/paper/missing-modality-robustness-in-semi","paper_url":"https://arxiv.org/abs/2304.10756v1","paper_title":"Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation","code":"https://github.com/harshm121/m3l","n_code_links":1,"syntology":null}],"since_archive":{"present":false,"note":"No Syntology-extracted rows are published in this build."},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}