BPDO:Boundary Points Dynamic Optimization for Arbitrary Shape Scene Text
  Detection
Jinzhi Zheng Libo Zhang Yanjun Wu Chen Zhao
Arbitrary shape scene text detection is of great importance in scene
understanding tasks. Due to the complexity and diversity of text in natural
scenes, existing scene text algorithms have limited accuracy for detecting
arbitrary shape text. In this paper, we propose a novel arbitrary shape scene
text detector through boundary points dynamic optimization(BPDO). The proposed
model is designed with a text aware module (TAM) and a boundary point dynamic
optimization module (DOM). Specifically, the model designs a text aware module
based on segmentation to obtain boundary points describing the central region
of the text by extracting a priori information about the text region. Then,
based on the idea of deformable attention, it proposes a dynamic optimization
model for boundary points, which gradually optimizes the exact position of the
boundary points based on the information of the adjacent region of each
boundary point. Experiments on CTW-1500, Total-Text, and MSRA-TD500 datasets
show that the model proposed in this paper achieves a performance that is
better than or comparable to the state-of-the-art algorithm, proving the
effectiveness of the model.