{"url":"/dataset/sintel-4d-lfv","name":"Sintel 4D LFV","full_name":"Sintel 4D Light Field Video Dataset","description_markdown":"A medium-scale synthetic 4D Light Field video dataset for depth (disparity) estimation. From the open-source movie Sintel. The dataset consists of 24 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20–50 frames, and has ground-truth disparity values, so that can be used for training deep learning-based methods. Each scene was rendered with a clean pass after modifying the production file of Sintel with reference to the MPI Sintel dataset.","description_withheld":null,"homepage":"https://ieee-dataport.org/open-access/sintel-4d-light-field-video-dataset","introduced_date":"2020-12-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/depth-estimation-from-4d-light-field-videos","title":"Depth estimation from 4D light field videos","first_author":"Takahiro Kinoshita","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[],"languages":[],"variants":["Sintel 4D LFV"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"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."}