{"url":"/dataset/kubric","name":"Kubric","full_name":null,"description_markdown":"**Kubric** is a data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.\r\n\r\nIt also presents a series of 13 different generated datasets for tasks ranging from studying 3D NeRF models to optical flow estimation.\r\n\r\n*Kubric is mainly built on-top of pybullet (for physics simulation) and Blender (for rendering); however, the code is kept modular to potentially support different rendering backends.*","description_withheld":null,"homepage":"https://github.com/google-research/kubric","introduced_date":"2022-03-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/kubric-a-scalable-dataset-generator","title":"Kubric: A scalable dataset generator","first_author":"Klaus Greff","url":null},"license":{"name":"Apache License 2.0","url":"https://github.com/google-research/kubric/blob/main/LICENSE"},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Visual Tracking","url":"/task/visual-tracking","datasets_with_task":"/datasets/task/visual-tracking"}],"languages":[],"variants":["Kubric"],"data_loaders":[],"num_papers_in_archive":77,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/visual-tracking-on-kubric","task":"Visual Tracking","dataset_variant":"Kubric","rows":2,"metrics":["Average Jaccard"],"first_row_in_archive_order":{"model":"TAPIR (Panning MOVi-E)","paper":"/paper/tapir-tracking-any-point-with-per-frame","metrics":{"Average Jaccard":"84.7"},"code_links":[{"title":"deepmind/tapnet","url":"https://github.com/deepmind/tapnet"},{"title":"riponazad/echotracker","url":"https://github.com/riponazad/echotracker"},{"title":"ibaiGorordo/Tapir-Pytorch-Inference","url":"https://github.com/ibaiGorordo/Tapir-Pytorch-Inference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/tapir-tracking-any-point-with-per-frame","title":"TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement","date":"2023-06-14","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":1,"samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"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."}