{"url":"/dataset/changesim","name":"ChangeSim","full_name":"ChangeSim","description_markdown":"**ChangeSim** is a dataset aimed at online scene change detection (SCD) and more. The data is collected in photo-realistic simulation environments with the presence of environmental non-targeted variations, such as air turbidity and light condition changes, as well as targeted object changes in industrial indoor environments. By collecting data in simulations, multi-modal sensor data and precise ground truth labels are obtainable such as the RGB image, depth image, semantic segmentation, change segmentation, camera poses, and 3D reconstructions. While the previous online SCD datasets evaluate models given well-aligned image pairs, ChangeSim also provides raw unpaired sequences that present an opportunity to develop an online SCD model in an end-to-end manner, considering both pairing and detection. Experiments show that even the latest pair-based SCD models suffer from the bottleneck of the pairing process, and it gets worse when the environment contains the non-targeted variations.","description_withheld":null,"homepage":"https://github.com/SAMMiCA/ChangeSim","introduced_date":"2021-03-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/changesim-towards-end-to-end-online-scene","title":"ChangeSim: Towards End-to-End Online Scene Change Detection in Industrial Indoor Environments","first_author":"Jin-Man Park","url":null},"license":{"name":"MIT","url":"https://github.com/SAMMiCA/ChangeSim/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"Change Detection","url":"/task/change-detection","datasets_with_task":"/datasets/task/change-detection"},{"name":"Scene Change Detection","url":"/task/scene-change-detection","datasets_with_task":"/datasets/task/scene-change-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ChangeSim"],"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/scene-change-detection-on-changesim","task":"Scene Change Detection","dataset_variant":"ChangeSim","rows":3,"metrics":["Category mIoU","macro F1"],"first_row_in_archive_order":{"model":"C-3PO","paper":"/paper/how-to-reduce-change-detection-to-semantic","metrics":{"Category mIoU":"27.8"},"code_links":[{"title":"DoctorKey/C-3PO","url":"https://github.com/DoctorKey/C-3PO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/change-detection-on-changesim-1","task":"Change Detection","dataset_variant":"ChangeSim","rows":1,"metrics":["Category mIoU"],"first_row_in_archive_order":{"model":"C-3PO","paper":"/paper/how-to-reduce-change-detection-to-semantic","metrics":{"Category mIoU":"27.8"},"code_links":[{"title":"DoctorKey/C-3PO","url":"https://github.com/DoctorKey/C-3PO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/how-to-reduce-change-detection-to-semantic","title":"How to Reduce Change Detection to Semantic Segmentation","date":"2022-06-15","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":1,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/changesim-towards-end-to-end-online-scene","title":"ChangeSim: Towards End-to-End Online Scene Change Detection in Industrial Indoor Environments","date":"2021-03-09","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":10,"samples_ran":1,"samples_unverified":9,"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."}