Action Sensitivity Learning for the Ego4D Episodic Memory Challenge 2023

Jiayi Shao; Ruijie Quan; Xiaohan Wang; Yi Yang

Action Sensitivity Learning for the Ego4D Episodic Memory Challenge 2023

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arxiv 2306.09172 v2 pith:JP47BGQS submitted 2023-06-15 cs.CV

Jiayi Shao , Xiaohan Wang , Ruijie Quan , Yi Yang This is my paper · ORCID

classification cs.CV

keywords querieschallengeactionego4depisodiclanguagelearningmemory

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This report presents ReLER submission to two tracks in the Ego4D Episodic Memory Benchmark in CVPR 2023, including Natural Language Queries and Moment Queries. This solution inherits from our proposed Action Sensitivity Learning framework (ASL) to better capture discrepant information of frames. Further, we incorporate a series of stronger video features and fusion strategies. Our method achieves an average mAP of 29.34, ranking 1st in Moment Queries Challenge, and garners 19.79 mean R1, ranking 2nd in Natural Language Queries Challenge. Our code will be released.

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Hier-EgoPack: Hierarchical Egocentric Video Understanding with Diverse Task Perspectives
cs.CV 2025-02 conditional novelty 5.0 of 10

Hier-EgoPack extends EgoPack's task-prototype transfer to multiple temporal granularities with a hierarchical GNN, improving Moment Queries and Long-Term Anticipation on Ego4D.

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