NMS Threshold matters for Ego4D Moment Queries -- 2nd place solution to the Ego4D Moment Queries Challenge 2023
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 11 references that are in the map. First posted on arXiv 5 Jul 2023.
Builds on
10 of 11 references.
References · 10
- 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,577
- 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,071
- 2017Soft-NMS -- Improving Object Detection With One Line of Codecited by 382
- 2022ActionFormer: Localizing Moments of Actions with Transformerscited by 311
- 2022Egocentric Video-Language Pretrainingcited by 232
- 2022Omnivore: A Single Model for Many Visual Modalitiescited by 215
- 2021OTA: Optimal Transport Assignment for Object Detectioncited by 178
- 2018Diagnosing Error in Temporal Action Detectorscited by 71
- 2022InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challengescited by 48
- 2022Where a Strong Backbone Meets Strong Features -- ActionFormer for Ego4D Moment Queries Challengecited by 3
Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.