{"url":"/dataset/msvwild863","name":"MSVWild863","full_name":null,"description_markdown":"WMVeID863 is captured with vehicles in motion with more challenges, such as motion blur,\r\nhuge background changes, and especially intense flare degradation from car lamps, and sunlight. It contains 863 identities of vehicle triplets (RGB, NI, and TI) captured with 8 camera views at a traffic checkpoint, contributing 14127 images.","description_withheld":null,"homepage":"","introduced_date":"2023-05-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/flare-aware-cross-modal-enhancement-network","title":"Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification","first_author":"Aihua Zheng","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["MSVWild863"],"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."}