{"url":"/dataset/2d-3d-match-dataset","name":"2D-3D Match Dataset","full_name":null,"description_markdown":"2D-3D Match Dataset is a new dataset of 2D-3D correspondences by leveraging the availability of several 3D datasets from RGB-D scans. Specifically, the data from SceneNN and 3DMatch are used. The training dataset consists of 110 RGB-D scans, of which 56 scenes are from SceneNN and 54 scenes are from 3DMatch. The 2D-3D correspondence data is generated as follows. Given a 3D point which is randomly sampled from a 3D point cloud, a set of 3D patches from different scanning views are extracted. To find a 2D-3D correspondence, for each 3D patch, its 3D position is re-projected into all RGB-D frames for which the point lies in the camera frustum, taking occlusion into account. The corresponding local 2D patches around the re-projected point are extracted. In total, around 1.4 millions 2D-3D correspondences are collected.\r\n\r\nSource: [2D-3D Match Dataset](https://github.com/hkust-vgd/lcd)","description_withheld":null,"homepage":"https://github.com/hkust-vgd/lcd","introduced_date":"2019-11-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/lcd-learned-cross-domain-descriptors-for-2d","title":"LCD: Learned Cross-Domain Descriptors for 2D-3D Matching","first_author":"Quang-Hieu Pham","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"3D Point Cloud Matching","url":"/task/3d-point-cloud-matching","datasets_with_task":"/datasets/task/3d-point-cloud-matching"}],"languages":[],"variants":["2D-3D Match Dataset"],"data_loaders":[{"repo":"https://github.com/hkust-vgd/lcd","url":"https://github.com/hkust-vgd/lcd","frameworks":["pytorch"]}],"num_papers_in_archive":27,"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."}