  This report describes our submission to the Ego4D Moment Queries Challenge
2023. Our submission extends ActionFormer, a latest method for temporal action
localization. Our extension combines an improved ground-truth assignment
strategy during training and a refined version of SoftNMS at inference time.
Our solution is ranked 2nd on the public leaderboard with 26.62% average mAP
and 45.69% Recall@1x at tIoU=0.5 on the test set, significantly outperforming
the strong baseline from 2023 challenge. Our code is available at
https://github.com/happyharrycn/actionformer_release.
