{"url":"/task/4d-panoptic-segmentation","name":"4D Panoptic Segmentation","slug":"4d-panoptic-segmentation","description_markdown":"**4D Panoptic Segmentation** is a computer vision task that extends [video panoptic segmentation](https://paperswithcode.com/task/video-panoptic-segmentation) to point cloud sequences. That is, given a point cloud sequence, the goal is to predict the semantic class of each point while consistently tracking object instances. Here, the points belonging to the same object instance should be assigned the same instance ID throughout the point cloud sequence. [LSTQ metric](https://arxiv.org/pdf/2102.12472.pdf) is used to evaluate the performance of this task. Video credit:    [Mask4Former](https://yilmazkadir.github.io/Mask4Former/)","categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":9,"papers_with_code":7,"benchmarks":1,"benchmark_tables_in_archive":1,"benchmark_tables_shown":1,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":3,"subtasks":0,"parent_tasks":0},"benchmarks":[{"leaderboard":"/sota/4d-panoptic-segmentation-on-semantickitti","slug":"4d-panoptic-segmentation-on-semantickitti","dataset":"SemanticKITTI","dataset_url":"/dataset/semantickitti","rows_in_archive":7,"metrics":["LSTQ"],"first_row_in_archive_order":{"model":"Mask4Former","paper_title":"Mask4Former: Mask Transformer for 4D Panoptic Segmentation","paper_url":"/paper/mask4d-mask-transformer-for-4d-panoptic","paper_date":"2023-09-28","arxiv_id":"2309.16133","code_links":[{"title":"YilmazKadir/Mask4Former","url":"https://github.com/YilmazKadir/Mask4Former"}],"syntology":null}}],"datasets":[{"url":"/dataset/semantickitti","name":"SemanticKITTI","full_name":"","num_papers_in_archive":669},{"url":"/dataset/4d-or","name":"4D-OR","full_name":"","num_papers_in_archive":11},{"url":"/dataset/mm-or","name":"MM-OR","full_name":"","num_papers_in_archive":3}],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":7,"of":7,"tagged_in_all":9,"items":[{"url":"/paper/4d-panoptic-scene-graph-generation-1","title":"4D Panoptic Scene Graph Generation","date":"2024-05-16","arxiv_id":"2405.10305","repositories_listed":3,"syntology":{"n":14,"n_ran":13,"n_unverified":1,"n_pointer_only":10}},{"url":"/paper/mask4d-mask-transformer-for-4d-panoptic","title":"Mask4Former: Mask Transformer for 4D Panoptic Segmentation","date":"2023-09-28","arxiv_id":"2309.16133","repositories_listed":1,"syntology":null},{"url":"/paper/mask4d-end-to-end-mask-based-4d-panoptic","title":"Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences","date":"2023-09-18","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/4d-stop-panoptic-segmentation-of-4d-lidar","title":"4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation","date":"2022-09-29","arxiv_id":"2209.14858","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_unverified":1,"n_pointer_only":3}},{"url":"/paper/lidar-based-4d-panoptic-segmentation-via","title":"LiDAR-based 4D Panoptic Segmentation via Dynamic Shifting Network","date":"2022-03-14","arxiv_id":"2203.07186","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_unverified":0,"n_pointer_only":2}},{"url":"/paper/contrastive-instance-association-for-4d","title":"Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans","date":"2021-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/4d-panoptic-lidar-segmentation","title":"4D Panoptic LiDAR Segmentation","date":"2021-02-24","arxiv_id":"2102.12472","repositories_listed":1,"syntology":null}],"syntology_records":3,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":1,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}