Text Shape
Text shape research focuses on accurately detecting, representing, and generating text in diverse forms, addressing challenges posed by complex shapes, varying orientations, and noisy environments. Current efforts concentrate on developing robust algorithms and model architectures, such as transformers and diffusion models, to improve the accuracy and efficiency of text detection and generation from various input modalities (e.g., images, text descriptions). This field is crucial for advancing document analysis, scene understanding, and 3D modeling applications, particularly in handling historical documents, real-world imagery, and creative design tools.
Papers
Real-time Scene Text Detection Based on Global Level and Word Level Features
Fuqiang Zhao, Jionghua Yu, Enjun Xing, Wenming Song, Xue Xu
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting
Seonghyeon Kim, Seung Shin, Yoonsik Kim, Han-Cheol Cho, Taeho Kil, Jaeheung Surh, Seunghyun Park, Bado Lee, Youngmin Baek