{"url":"/dataset/coconut","name":"COCONut","full_name":null,"description_markdown":"The COCONut dataset is a modernized segmentation dataset that builds upon the established COCO benchmark. It aims to address the limitations of the original COCO segmentation annotations by enhancing annotation quality and expanding the dataset to encompass a larger number of images with high-quality masks. COCONut harmonizes segmentation annotations across semantic, instance, and panoptic segmentation tasks, providing meticulously crafted masks for improved accuracy and consistency. It includes 383K images with more than 5.18M panoptic masks, making it a large-scale universal segmentation dataset verified by human raters [T1], [T6].","description_withheld":null,"homepage":"https://xdeng7.github.io/coconut.github.io","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["COCONut"],"data_loaders":[],"num_papers_in_archive":0,"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."}