LP-IOANET: EFFICIENT HIGH RESOLUTION DOCUMENT SHADOW REMOVAL

Document shadow removal is an integral task in document enhancement pipelines, as it improves visibility, readability and thus the overall quality. Assuming that the majority of real-life document shadow removal scenarios require real-time, accurate models that can produce high-resolution outputs in-the- wild, we propose Laplacian Pyramid with Input/Output Attention Network (LP-IOANet), a novel pipeline with a lightweight architecture and an upsampling module. Furthermore, to further improve our accuracy, we propose three new datasets which cover a wide range of lighting conditions, images, shadow shapes and viewpoints. Our results show that we outperform the state-of-the-art by a 35% relative improvement in mean average error (MAE), while running real-time with x4 the resolution on a mobile device.