no code implementations • 1 May 2023 • Youngmin Baek, Daehyun Nam, Jaeheung Surh, Seung Shin, Seonghyeon Kim
In this work, we analyze the natural characteristics of a table, where a table is composed of cells and each cell is made up of borders consisting of edges.
no code implementations • 10 Mar 2022 • Seonghyeon Kim, Seung Shin, Yoonsik Kim, Han-Cheol Cho, Taeho Kil, Jaeheung Surh, Seunghyun Park, Bado Lee, Youngmin Baek
Since only a single point is required to recognize the text, the proposed method enables text spotting without an arbitrarily-shaped detector or bounding polygon annotations.
Ranked #7 on Text Spotting on Total-Text
no code implementations • 23 Jul 2021 • Junyeop Lee, Yoonsik Kim, Seonghyeon Kim, Moonbin Yim, Seung Shin, Gayoung Lee, Sungrae Park
Scene text editing (STE), which converts a text in a scene image into the desired text while preserving an original style, is a challenging task due to a complex intervention between text and style.
no code implementations • ECCV 2020 • Youngmin Baek, Seung Shin, Jeonghun Baek, Sungrae Park, Junyeop Lee, Daehyun Nam, Hwalsuk Lee
This architecture is formed by utilizing detection outputs in the recognizer and propagating the recognition loss through the detection stage.
1 code implementation • 11 Jun 2020 • Youngmin Baek, Daehyun Nam, Sungrae Park, Junyeop Lee, Seung Shin, Jeonghun Baek, Chae Young Lee, Hwalsuk Lee
We believe that our metrics can play a key role in developing and analyzing state-of-the-art text detection and recognition methods.
1 code implementation • NeurIPS Workshop Document_Intelligen 2019 • Seunghyun Park, Seung Shin, Bado Lee, Junyeop Lee, Jaeheung Surh, Minjoon Seo, Hwalsuk Lee
OCR is inevitably linked to NLP since its final output is in text.