{"url":"/dataset/grasp-anything","name":"Grasp-Anything","full_name":null,"description_markdown":"We leverage knowledge from foundation models to introduce Grasp-Anything, a new large-scale dataset with 1M (one million) samples and 3M objects, substantially surpassing prior datasets in diversity and magnitude.  In addition, Grasp-Anything can universally cover objects in our daily lives and offer a great range of object diversity.","description_withheld":null,"homepage":"https://airvlab.github.io/grasp-anything/","introduced_date":"2023-09-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/grasp-anything-large-scale-grasp-dataset-from","title":"Grasp-Anything: Large-scale Grasp Dataset from Foundation Models","first_author":"An Dinh Vuong","url":null},"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode"},"modalities":[],"tasks":[{"name":"Robotic Grasping","url":"/task/robotic-grasping","datasets_with_task":"/datasets/task/robotic-grasping"}],"languages":[],"variants":["Grasp-Anything"],"data_loaders":[],"num_papers_in_archive":5,"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."}