{"url":"/dataset/bl30k","name":"BL30K","full_name":null,"description_markdown":"BL30K is a synthetic dataset rendered using Blender with ShapeNet's data. We break the dataset into six segments, each with approximately 5K videos. The videos are organized in a similar format as DAVIS and YouTubeVOS, so dataloaders for those datasets can be used directly. Each video is 160 frames long, and each frame has a resolution of 768*512. There are 3-5 objects per video, and each object has a random smooth trajectory -- we tried to optimize the trajectories in a greedy fashion to minimize object intersection (not guaranteed), with occlusions still possible (happen a lot in reality). See [MiVOS](https://github.com/hkchengrex/MiVOS) for details.","description_withheld":null,"homepage":"https://github.com/hkchengrex/MiVOS","introduced_date":"2021-03-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/modular-interactive-video-object-segmentation","title":"Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion","first_author":"Ho Kei Cheng","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Video Object Segmentation","url":"/task/video-object-segmentation","datasets_with_task":"/datasets/task/video-object-segmentation"},{"name":"Semi-Supervised Video Object Segmentation","url":"/task/semi-supervised-video-object-segmentation","datasets_with_task":"/datasets/task/semi-supervised-video-object-segmentation"},{"name":"Unsupervised Video Object Segmentation","url":"/task/unsupervised-video-object-segmentation","datasets_with_task":"/datasets/task/unsupervised-video-object-segmentation"},{"name":"Video Object Tracking","url":"/task/video-object-tracking","datasets_with_task":"/datasets/task/video-object-tracking"},{"name":"Interactive Video Object Segmentation","url":"/task/interactive-video-object-segmentation","datasets_with_task":"/datasets/task/interactive-video-object-segmentation"}],"languages":[],"variants":["BL30K"],"data_loaders":[{"repo":"https://github.com/hkchengrex/MiVOS","url":"https://github.com/hkchengrex/MiVOS","frameworks":["pytorch"]}],"num_papers_in_archive":11,"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."}