activity
20192021
most citedCharacter Region Attention For Text Spotting

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels

Jeonghun Baek, Yusuke Matsui, Kiyoharu Aizawa

Scene text recognition (STR) task has a common practice: All state-of-the-art STR models are trained on large synthetic data. In contrast to this practice, training STR models only…

cs.CV20203 cited

Character Region Attention For Text Spotting

Youngmin Baek, Seung Shin, Jeonghun Baek +4

A scene text spotter is composed of text detection and recognition modules. Many studies have been conducted to unify these modules into an end-to-end trainable model to achieve be…

cs.CV2020

CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks

Youngmin Baek, Daehyun Nam, Sungrae Park +5

Despite the recent success of text detection and recognition methods, existing evaluation metrics fail to provide a fair and reliable comparison among those methods. In addition, t…

cs.CV2019

On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention

Junyeop Lee, Sungrae Park, Jeonghun Baek +3

Scene text recognition (STR) is the task of recognizing character sequences in natural scenes. While there have been great advances in STR methods, current methods still fail to re…

cs.CV2019

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

Jeonghun Baek, Geewook Kim, Junyeop Lee +5

Many new proposals for scene text recognition (STR) models have been introduced in recent years. While each claim to have pushed the boundary of the technology, a holistic and fair…