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This paper presents our solution for the ICDAR 2021 Competition on ScientificTable Image Recognition to LaTeX. This competition has two sub-tasks: TableStructure Reconstruction (TSR) and Table Content Reconstruction (TCR). We treatboth sub-tasks as two individual image-to-sequence recognition problems. Weleverage our previously proposed algorithm MASTER \cite{lu2019master}, which isoriginally proposed for scene text recognition. We optimize the MASTER modelfrom several perspectives: network structure, optimizer, normalization method,pre-trained model, resolution of input image, data augmentation, and modelensemble. Our method achieves 0.7444 Exact Match and 0.8765 Exact Match @95\%on the TSR task, and obtains 0.5586 Exact Match and 0.7386 Exact Match 95\% onthe TCR task.

PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Table Image Recognition to Latex