{"url":"/dataset/nyu-vp","name":"NYU-VP","full_name":null,"description_markdown":"NYU-VP is a new dataset for multi-model fitting, vanishing point (VP) estimation in this case. Each image is annotated with up to eight vanishing points, and pre-extracted line segments are provided which act as data points for a robust estimator. Due to its size, the dataset is the first to allow for supervised learning of a multi-model fitting task.\r\n\r\nSource: [CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus](https://arxiv.org/pdf/2001.02643.pdf)","description_withheld":null,"homepage":"https://github.com/fkluger/nyu_vp","introduced_date":"2020-01-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/consac-robust-multi-model-fitting-by","title":"CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus","first_author":"Florian Kluger","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Self-Supervised Learning","url":"/task/self-supervised-learning","datasets_with_task":"/datasets/task/self-supervised-learning"},{"name":"Homography Estimation","url":"/task/homography-estimation","datasets_with_task":"/datasets/task/homography-estimation"}],"languages":[],"variants":["NYU-VP"],"data_loaders":[{"repo":"https://github.com/fkluger/nyu_vp","url":"https://github.com/fkluger/nyu_vp","frameworks":[]}],"num_papers_in_archive":5,"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."}