Self-supervised Character-to-Character Distillation for Text Recognition
Self-supervised Character-to-Character Distillation for Text Recognition
When handling complicated text images (e.g., irregular structures, low resolution, heavy occlusion, and uneven illumination), existing supervised text recognition methods are data-hungry. Although these methods employ large-scale synthetic text images to reduce the dependence on annotated real images, the domain gap still limits the recognition performance. Therefore, exploring the robust …