{"url":"/dataset/vot2022","name":"VOT2022","full_name":null,"description_markdown":"Click to add a brief description of the dataset (Markdown and LaTeX enabled).\r\n\r\nProvide:\r\n\r\n* a high-level explanation of the dataset characteristics\r\n* explain motivations and summary of its content\r\n* potential use cases of the dataset","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Visual Object Tracking","url":"/task/visual-object-tracking","datasets_with_task":"/datasets/task/visual-object-tracking"}],"languages":[],"variants":["VOT2022"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/visual-object-tracking-on-vot2022","task":"Visual Object Tracking","dataset_variant":"VOT2022","rows":5,"metrics":["EAO"],"first_row_in_archive_order":{"model":"DAM4SAM","paper":"/paper/a-distractor-aware-memory-for-visual-object","metrics":{"EAO":"0.753"},"code_links":[{"title":"jovanavidenovic/dam4sam","url":"https://github.com/jovanavidenovic/dam4sam"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a-distractor-aware-memory-for-visual-object","title":"A Distractor-Aware Memory for Visual Object Tracking with SAM2","date":"2024-11-26","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":3,"samples_unverified":8,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/2408-00714","title":"SAM 2: Segment Anything in Images and Videos","date":"2024-08-01","rows_on_this_dataset":1,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":49,"samples_ran":28,"samples_unverified":21,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/diffusiontrack-point-set-diffusion-model-for","title":"DiffusionTrack: Point Set Diffusion Model for Visual Object Tracking","date":"2024-01-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/mixformer-end-to-end-tracking-with-iterative-2","title":"MixFormer: End-to-End Tracking with Iterative Mixed Attention","date":"2023-02-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/associating-objects-with-transformers-for","title":"Associating Objects with Transformers for Video Object Segmentation","date":"2021-06-04","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":60,"samples_ran":31,"samples_unverified":29,"pointer_only_for_licence":11,"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."}