5 papers with code • 10 benchmarks • 4 datasets
Despite the large number of both commercial and academic methods for Automatic License Plate Recognition (ALPR), most existing approaches are focused on a specific license plate (LP) region (e. g. European, US, Brazilian, Taiwanese, etc.
Ranked #2 on License Plate Recognition on AOLP-RP
This paper proposes LPRNet - end-to-end method for Automatic License Plate Recognition without preliminary character segmentation.
Ranked #1 on License Plate Recognition on Chinese License Plates
Unconstrained text recognition is an important computer vision task, featuring a wide variety of different sub-tasks, each with its own set of challenges.
Although most current license plate (LP) recognition applications have been significantly advanced, they are still limited to ideal environments where training data are carefully annotated with constrained scenes.
Ranked #3 on License Plate Recognition on AOLP-RP
First, in the SSIG dataset, composed of 2, 000 frames from 101 vehicle videos, our system achieved a recognition rate of 93. 53% and 47 Frames Per Second (FPS), performing better than both Sighthound and OpenALPR commercial systems (89. 80% and 93. 03%, respectively) and considerably outperforming previous results (81. 80%).
Ranked #2 on License Plate Recognition on SSIG-SegPlate