{"url":"/dataset/grasping-dataset-suction-based","name":"Grasping dataset: suction-based","full_name":"suction-based-grasping-dataset","description_markdown":"A small and simple dataset featuring RGB-D images and heightmaps of various objects in a bin with manually annotated suctionable regions","description_withheld":null,"homepage":"https://vision.princeton.edu/projects/2017/arc/","introduced_date":"2018-03-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/realtime-global-attention-network-for","title":"Realtime Global Attention Network for Semantic Segmentation","first_author":"Xi Mo","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Grasping dataset: suction-based"],"data_loaders":[],"num_papers_in_archive":2,"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."}