{"url":"/dataset/vreloc","name":"vReLoc","full_name":null,"description_markdown":"A total of 18 sequences were collected of various lengths. Since the Velodyne LiDAR, RealSense camera and Vicon motion tracker system run in different frequencies, we synchronized these systems so that the image and LiDAR in each timestamp has the same 6-DoF pose. For the static scenario, there are no moving objects in the scene. For other scenarios, there are people randomly walking in the scene. Sequences 01-10 come from the static environment, sequences 11-15 are the one-person moving scenario, and sequences 16-18 are two-persons moving scenario.","description_withheld":null,"homepage":"https://github.com/loveoxford/vReLoc","introduced_date":"2020-03-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/pointloc-deep-pose-regressor-for-lidar-point","title":"PointLoc: Deep Pose Regressor for LiDAR Point Cloud Localization","first_author":null,"url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["vReLoc"],"data_loaders":[],"num_papers_in_archive":2,"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."}