  In this technical report, we present our 1st place solution for the ICDAR
2021 competition on mathematical formula detection (MFD). The MFD task has
three key challenges including a large scale span, large variation of the ratio
between height and width, and rich character set and mathematical expressions.
Considering these challenges, we used Generalized Focal Loss (GFL), an
anchor-free method, instead of the anchor-based method, and prove the Adaptive
Training Sampling Strategy (ATSS) and proper Feature Pyramid Network (FPN) can
well solve the important issue of scale variation. Meanwhile, we also found
some tricks, e.g., Deformable Convolution Network (DCN), SyncBN, and Weighted
Box Fusion (WBF), were effective in MFD task. Our proposed method ranked 1st in
the final 15 teams.
