  The goal of AVA challenge is to provide vision-based benchmarks and methods
relevant to accessibility. In this paper, we introduce the technical details of
our submission to the CVPR2022 AVA Challenge. Firstly, we conducted some
experiments to help employ proper model and data augmentation strategy for this
task. Secondly, an effective training strategy was applied to improve the
performance. Thirdly, we integrated the results from two different segmentation
frameworks to improve the performance further. Experimental results demonstrate
that our approach can achieve a competitive result on the AVA test set.
Finally, our approach achieves 63.008\%AP@0.50:0.95 on the test set of CVPR2022
AVA Challenge.
