{"url":"/dataset/armbench","name":"ARMBench","full_name":null,"description_markdown":"**ARMBench** is a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. ARMBench contains images, videos, and metadata that corresponds to 235K+ pick-and-place activities on 190K+ unique objects. The data is captured at different stages of manipulation, i.e., pre-pick, during transfer, and after placement.\r\n\r\nSource: [ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation](https://arxiv.org/pdf/2303.16382v1.pdf)\r\n\r\nImage Source: [ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation](https://arxiv.org/pdf/2303.16382v1.pdf)","description_withheld":null,"homepage":"http://armbench.s3-website-us-east-1.amazonaws.com/index.html","introduced_date":"2023-03-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/armbench-an-object-centric-benchmark-dataset","title":"ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation","first_author":"Chaitanya Mitash","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"Video Object Segmentation","url":"/task/video-object-segmentation","datasets_with_task":"/datasets/task/video-object-segmentation"},{"name":"Defect Detection","url":"/task/defect-detection","datasets_with_task":"/datasets/task/defect-detection"}],"languages":[],"variants":["ARMBench"],"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/instance-segmentation-on-armbench","task":"Instance Segmentation","dataset_variant":"ARMBench","rows":7,"metrics":["AP50","AP75"],"first_row_in_archive_order":{"model":"RISE (VIT-B)","paper":"/paper/robot-instance-segmentation-with-few","metrics":{"AP50":"86.37","AP75":"77.51"},"code_links":[{"title":"mkimhi/RISE","url":"https://github.com/mkimhi/RISE"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/robot-instance-segmentation-with-few","title":"Robot Instance Segmentation with Few Annotations for Grasping","date":"2024-07-01","rows_on_this_dataset":5,"code_links":1,"syntology":null},{"paper":"/paper/robollm-robotic-vision-tasks-grounded-on","title":"RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models","date":"2023-10-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/armbench-an-object-centric-benchmark-dataset","title":"ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation","date":"2023-03-29","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"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."}