{"url":"/dataset/iphone-dataset-monocular-dynamic-view","name":"iPhone (Monocular Dynamic View Synthesis)","full_name":null,"description_markdown":"iPhone dataset is a challenging benchmarks for dynamic reconstruction. This dataset consists of a collection of videos with realistic scenes and large object motions captured with a hand-held iPhone. The evaluation measures rendering quality on novel viewpoints which have low overlaps with the training camera views. This datasets do not have the (a) teleporting camera motion or (b) quasi-static scene motion issues as the previous ones.","description_withheld":null,"homepage":"https://kair-bair.github.io/dycheck/","introduced_date":"2022-05-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/monocular-dynamic-view-synthesis-a-reality","title":"Monocular Dynamic View Synthesis: A Reality Check","first_author":"Hang Gao","url":null},"license":{"name":"Apache 2.0","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Dynamic Reconstruction","url":"/task/dynamic-reconstruction","datasets_with_task":"/datasets/task/dynamic-reconstruction"}],"languages":[],"variants":["iPhone (Monocular Dynamic View Synthesis)"],"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/dynamic-reconstruction-on-iphone-dataset","task":"Dynamic Reconstruction","dataset_variant":"iPhone (Monocular Dynamic View Synthesis)","rows":7,"metrics":["LPIPS"],"first_row_in_archive_order":{"model":"MB-GS","paper":"/paper/motion-blender-gaussian-splatting-for-dynamic","metrics":{"LPIPS":"0.37"},"code_links":[{"title":"mlzxy/motion-blender-gs","url":"https://github.com/mlzxy/motion-blender-gs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/motion-blender-gaussian-splatting-for-dynamic","title":"Motion Blender Gaussian Splatting for Dynamic Scene Reconstruction","date":"2025-03-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/shape-of-motion-4d-reconstruction-from-a","title":"Shape of Motion: 4D Reconstruction from a Single Video","date":"2024-07-18","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/4d-gaussian-splatting-for-real-time-dynamic","title":"4D Gaussian Splatting for Real-Time Dynamic Scene Rendering","date":"2023-10-12","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":6,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deformable-3d-gaussians-for-high-fidelity","title":"Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction","date":"2023-09-22","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":4,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dynibar-neural-dynamic-image-based-rendering","title":"DynIBaR: Neural Dynamic Image-Based Rendering","date":"2022-11-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/monocular-dynamic-view-synthesis-a-reality","title":"Monocular Dynamic View Synthesis: A Reality Check","date":"2022-10-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hypernerf-a-higher-dimensional-representation","title":"HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields","date":"2021-06-24","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":1,"samples_unverified":14,"pointer_only_for_licence":0,"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":5,"samples_harvested":39,"samples_ran":13,"samples_unverified":26,"pointer_only_for_licence":2,"papers_with_no_sample_that_ran":1,"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."}