Search Results for author: Bado Lee

Found 9 papers, 8 papers with code

DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting

no code implementations10 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.

Text Spotting

Few-shot Font Generation with Weakly Supervised Localized Representations

2 code implementations22 Dec 2021 Song Park, Sanghyuk Chun, Junbum Cha, Bado Lee, Hyunjung Shim

Existing methods learn to disentangle style and content elements by developing a universal style representation for each font style.

Font Generation

Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts

4 code implementations ICCV 2021 Song Park, Sanghyuk Chun, Junbum Cha, Bado Lee, Hyunjung Shim

MX-Font extracts multiple style features not explicitly conditioned on component labels, but automatically by multiple experts to represent different local concepts, e. g., left-side sub-glyph.

Disentanglement Font Generation +1

Few-shot Font Generation with Localized Style Representations and Factorization

3 code implementations23 Sep 2020 Song Park, Sanghyuk Chun, Junbum Cha, Bado Lee, Hyunjung Shim

However, learning component-wise styles solely from reference glyphs is infeasible in the few-shot font generation scenario, when a target script has a large number of components, e. g., over 200 for Chinese.

Font Generation

Few-shot Compositional Font Generation with Dual Memory

3 code implementations ECCV 2020 Junbum Cha, Sanghyuk Chun, Gayoung Lee, Bado Lee, Seonghyeon Kim, Hwalsuk Lee

By utilizing the compositionality of compositional scripts, we propose a novel font generation framework, named Dual Memory-augmented Font Generation Network (DM-Font), which enables us to generate a high-quality font library with only a few samples.

Font Generation

Character Region Awareness for Text Detection

18 code implementations CVPR 2019 Youngmin Baek, Bado Lee, Dongyoon Han, Sangdoo Yun, Hwalsuk Lee

Scene text detection methods based on neural networks have emerged recently and have shown promising results.

 Ranked #1 on Scene Text Detection on ICDAR 2013 (Precision metric)

Scene Text Detection Text Detection

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