Forensic License Plate Recognition with Compression-Informed Transformers

arXiv:2207.14686v3 Announce Type: replace
Abstract: Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e.g., from surveillance cameras. In this work, we propose a side-informed Transformer architecture that embeds knowledge on the input compression level to improve recognition under strong compression. We show the effectiveness of Transformers for license plate recognition (LPR) on a low-quality real-world dataset. …

abstract architecture arxiv cameras challenge compression cs.ai cs.cv investigations knowledge legal license low recognition resolution surveillance transformer transformer architecture transformers type work