ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment

• URL: http://arxiv.org/abs/2107.05279v1
• Date: Mon, 12 Jul 2021 09:29:02 GMT
• Title: ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment
• Authors: Chun Chet Ng, Akmalul Khairi Bin Nazaruddin, Yeong Khang Lee, Xinyu Wang, Yuliang Liu, Chee Seng Chan, Lianwen Jin, Yipeng Sun, and Lixin Fan
• Abstract summary: The ICText dataset is the main target for the proposed Robust Reading Challenge on Integrated Circuit Text Spotting and Aesthetic Assessment (RRC-ICText) 2021. The entire competition has received a total of 233 submissions from 10 unique teams/individuals. Details of the competition and submission results are presented in this report.
• Score: 46.25545473730335
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With hundreds of thousands of electronic chip components are being manufactured every day, chip manufacturers have seen an increasing demand in seeking a more efficient and effective way of inspecting the quality of printed texts on chip components. The major problem that deters this area of research is the lacking of realistic text on chips datasets to act as a strong foundation. Hence, a text on chips dataset, ICText is used as the main target for the proposed Robust Reading Challenge on Integrated Circuit Text Spotting and Aesthetic Assessment (RRC-ICText) 2021 to encourage the research on this problem. Throughout the entire competition, we have received a total of 233 submissions from 10 unique teams/individuals. Details of the competition and submission results are presented in this report.

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