{"url":"/dataset/synpick","name":"SynPick","full_name":null,"description_markdown":"SynPick is a synthetic dataset for dynamic scene understanding in bin-picking scenarios. In contrast to existing datasets, this dataset is both situated in a realistic industrial application domain -- inspired by the well-known Amazon Robotics Challenge (ARC) -- and features dynamic scenes with authentic picking actions as chosen by our picking heuristic developed for the ARC 2017. The dataset is compatible with the popular BOP dataset format.\r\n\r\nThe dataset consists of 21 Synthetic videos with 503,232 with diverse lightning and 3 different views of each video.","description_withheld":null,"homepage":"http://ais.uni-bonn.de/datasets/synpick/","introduced_date":"2021-07-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/synpick-a-dataset-for-dynamic-bin-picking","title":"SynPick: A Dataset for Dynamic Bin Picking Scene Understanding","first_author":"Arul Selvam Periyasamy","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Scene Understanding","url":"/task/scene-understanding","datasets_with_task":"/datasets/task/scene-understanding"},{"name":"Video Prediction","url":"/task/video-prediction","datasets_with_task":"/datasets/task/video-prediction"}],"languages":[],"variants":["SynPick","SynpickVP"],"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/video-prediction-on-synpickvp","task":"Video Prediction","dataset_variant":"SynpickVP","rows":5,"metrics":["LPIPS","MSE","PSNR","SSIM"],"first_row_in_archive_order":{"model":"MSPred","paper":"/paper/video-prediction-at-multiple-scales-with","metrics":{"LPIPS":"0.033","MSE":"53.09","PSNR":"27.89","SSIM":"0.881"},"code_links":[{"title":"AIS-Bonn/MSPred","url":"https://github.com/AIS-Bonn/MSPred"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/video-prediction-at-multiple-scales-with","title":"MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks","date":"2022-03-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/disentangling-physical-dynamics-from-unknown","title":"Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction","date":"2020-03-03","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+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."}},{"paper":"/paper/predrnn-towards-a-resolution-of-the-deep-in","title":"PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning","date":"2018-04-17","rows_on_this_dataset":1,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":0,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/stochastic-video-generation-with-a-learned","title":"Stochastic Video Generation with a Learned Prior","date":"2018-02-21","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":10,"samples_ran":1,"samples_unverified":9,"pointer_only_for_licence":2,"papers_with_no_sample_that_ran":2,"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."}