activity
20172021
most citedShow, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching

9 citations · 14 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV2021

SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models

Moonbin Yim, Yoonsik Kim, Han-Cheol Cho +1

For successful scene text recognition (STR) models, synthetic text image generators have alleviated the lack of annotated text images from the real world. Specifically, they genera…

cs.LG20219 cited

Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching

Mingi Ji, Byeongho Heo, Sungrae Park

Knowledge distillation extracts general knowledge from a pre-trained teacher network and provides guidance to a target student network. Most studies manually tie intermediate featu…

cs.LG2021

SWAD: Domain Generalization by Seeking Flat Minima

Junbum Cha, Sanghyuk Chun, Kyungjae Lee +4

Domain generalization (DG) methods aim to achieve generalizability to an unseen target domain by using only training data from the source domains. Although a variety of DG methods…

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…