Adversarial Generation of Training Examples: Applications to Moving Vehicle License Plate Recognition

Understand

Generative Adversarial Networks (GAN) have attracted much research attention recently, leading to impressive results for natural image generation.

• However, to date little success was observed in using GAN generated images for improving classification tasks.
• Here we attempt to explore, in the context of car license plate recognition, whether it is possible to generate synthetic training data using GAN to improve recognition accuracy.
• With a carefully-designed pipeline, we show that the answer is affirmative.