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This dataset contains raw video and music files from the MGSV-EC benchmark. Due to copyright and redistribution restrictions (content sourced from Kuaishou and third-party creators), access is granted only for non-commercial academic research purposes. By requesting access, you agree to the following terms.

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MGSV-EC Raw Media

Raw video and music files for the MGSV-EC benchmark, accompanying the paper:

Music Grounding by Short Video (ICCV 2025)

The official repository at xxayt/MGSV provides annotations, pre-extracted features, and code. This repository supplements it with the original media files to enable research on new video-audio grounding, encoder, or end-to-end methods.

Access

This is a gated dataset with manual review. Request access above.

Data Coverage

The full MGSV-EC benchmark contains 53,194 videos paired with 4,050 unique music tracks. This repository provides a partial release of the raw media due to source platform restrictions:

Type Files in this repo Full dataset
Music tracks 7,580 (incl. vocal/no-vocal variants) 4,050 unique tracks
Test videos 1,721 2,000
Train/Val videos 2,085 51,194

Pre-extracted features (ViT-B-32 CLIP visual + AST audio) for all 53,194 entries are available at xxayt/MGSV-EC. For reproducing the benchmark results reported in the paper, the pre-extracted features are sufficient.

Files

Directory File Size Description
raw_music/ music.tar.gz.00 25 GB All music tracks (split archive, 1 part)
raw_videos/ test_videos.tar.gz.{00,01,02} 109 GB Test set videos (split archive, 3 parts)
raw_videos/ trainval_videos.tar.gz.{00,01,02} 128 GB Train/val set videos (split archive, 3 parts)
Total 7 files ~261 GB

Download & Extract

# Download via huggingface-cli
huggingface-cli download xxayt/MGSV-EC-Raw --repo-type dataset --local-dir MGSV-EC-Raw

# Extract music
cd MGSV-EC-Raw/raw_music
cat music.tar.gz.* | tar -xzf -

# Extract test videos
cd ../raw_videos
cat test_videos.tar.gz.* | tar -xzf -

# Extract train/val videos
cat trainval_videos.tar.gz.* | tar -xzf -

Terms of Use

  • Non-commercial academic research only. Commercial use requires contacting the authors.
  • No redistribution. Do not share the downloaded files or any derived copies.
  • Citation required. Please cite the MGSV paper in any published work.
  • Licensed under CC BY-NC-ND 4.0.

Citation

@inproceedings{xin2025mgsv,
  title={Music Grounding by Short Video},
  author={Xin, Zijie and Wang, Minquan and Liu, Jingyu and Chen, Quan and Ma, Ye and Jiang, Peng and Li, Xirong},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  year={2025}
}

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