33 citations · 33 across the 3 of their papers we have counts for
3 papers
Joint Low-level and High-level Textual Representation Learning with Multiple Masking Strategies
Zhengmi Tang, Yuto Mitsui, Tomo Miyazaki +1
Most existing text recognition methods are trained on large-scale synthetic datasets due to the scarcity of labeled real-world datasets. Synthetic images, however, cannot faithfull…
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +3
Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhan…
Stroke-Based Scene Text Erasing Using Synthetic Data for Training
Zhengmi Tang, Tomo Miyazaki, Yoshihiro Sugaya +1
Scene text erasing, which replaces text regions with reasonable content in natural images, has drawn significant attention in the computer vision community in recent years. There a…