Long-Form Multi-Person Video Dataset for Group Action Quality Assessment

The core message of this paper is to construct the first multi-person long-form video dataset, LOGO, for action quality assessment, and propose a group-aware module, GOAT, to build relations among multiple actors and fuse the temporal representations based on spatial information, which achieves substantial improvements compared to existing methods.