  Semantic segmentation is an important task in computer vision, from which
some important usage scenarios are derived, such as autonomous driving, scene
parsing, etc. Due to the emphasis on the task of video semantic segmentation,
we participated in this competition. In this report, we briefly introduce the
solutions of team 'BetterThing' for the ICCV2021 - Video Scene Parsing in the
Wild Challenge. Transformer is used as the backbone for extracting video frame
features, and the final result is the aggregation of the output of two
Transformer models, SWIN and VOLO. This solution achieves 57.3% mIoU, which is
ranked 3rd place in the Video Scene Parsing in the Wild Challenge.
