most citedNTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

9 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

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…

eess.IV20209 cited

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

Kai Zhang, Shuhang Gu, Radu Timofte +60

This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…

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…