Soccer-GMR NDA Form
Please fill in the following NDA form with accurate information and agree to the non-commercial, no-redistribution, and rights-compliance terms before requesting access.
By requesting access to Soccer-GMR, you agree to use the dataset only for non-commercial research or educational purposes. You also agree not to redistribute, mirror, sell, or make the dataset publicly downloadable. The dataset may contain or reference third-party football match content,and you are responsible for complying with all applicable rights, licenses,and platform terms.
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Access and NDA Terms
Soccer-GMR is available through gated access on Hugging Face. Access is manually reviewed after the requester completes the Soccer-GMR NDA form. Commercial use, redistribution, public hosting, or sharing access links is not permitted.
Soccer-GMR
This repository hosts large assets for Soccer-GMR, a dataset introduced in Retrieving Any Relevant Moments: Benchmark and Models for Generalized Moment Retrieval.
- Paper: https://arxiv.org/abs/2605.02623
- Code: https://github.com/dymm9977/generalized-moment-retrieval
- Project page: https://dymm9977.github.io/generalized-moment-retrieval/
Contents
Currently available:
| File | Description |
|---|---|
SoccerReplay-GMR.tar |
Processed Soccer-GMR video clips constructed from the SoccerReplay-1988 source data. |
SportsMoments-GMR.tar |
Processed Soccer-GMR video clips constructed from the SportsMoments source data. |
WC2022-GMR.tar |
Processed Soccer-GMR video clips constructed from the World Cup 2022 source data. |
Planned uploads:
| File / Directory | Description |
|---|---|
checkpoints/ |
Model weights released with the paper. |
Labels, evaluation code, data format documentation, and usage examples are maintained in the GitHub repository.
Note
Soccer-GMR is built by adapting soccer video sources and their timestamp/caption annotations into the Generalized Moment Retrieval format. Please follow the usage terms of the corresponding upstream sources when using the video archives.
Citation
@article{ding2026retrieving,
title={Retrieving Any Relevant Moments: Benchmark and Models for Generalized Moment Retrieval},
author={Ding, Yiming and Cao, Siyu and Jiao, Luyuan and Li, Yixuan and Wang, Zitong and Liu, Zhiyong and Zhang, Lu},
journal={arXiv preprint arXiv:2605.02623},
year={2026},
doi={10.48550/arXiv.2605.02623}
}
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