{"url":"/dataset/maniskill","name":"ManiSkill","full_name":null,"description_markdown":"ManiSkill is a large-scale learning-from-demonstrations benchmark for articulated object manipulation with visual input (point cloud and image). ManiSkill supports object-level variations by utilizing a rich and diverse set of articulated objects, and each task is carefully designed for learning manipulations on a single category of objects. ManiSkill is equipped with high-quality demonstrations to facilitate learning-from-demonstrations approaches and perform evaluations on common baseline algorithms. ManiSkill can encourage the robot learning community to explore more on learning generalizable object manipulation skills.\r\n\r\nSource: [ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills](https://paperswithcode.com/paper/maniskill-learning-from-demonstrations)\r\n\r\nImage source: [ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills](https://arxiv.org/pdf/2107.14483v1.pdf)","description_withheld":null,"homepage":"https://github.com/haosulab/ManiSkill","introduced_date":"2021-07-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/maniskill-learning-from-demonstrations","title":"ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations","first_author":"Tongzhou Mu","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[],"languages":[],"variants":["ManiSkill"],"data_loaders":[],"num_papers_in_archive":38,"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."}