NMS Threshold matters for Ego4D Moment Queries -- 2nd place solution to
  the Ego4D Moment Queries Challenge 2023
Lin Sui Fangzhou Mu Yin Li
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.