| --- |
| license: other |
| license_name: mixed-third-party-licenses |
| license_link: LICENSE |
| configs: |
| - config_name: events |
| default: true |
| data_files: |
| - split: events |
| path: metadata/events.parquet |
| - split: sample_events |
| path: samples/metadata/events.parquet |
| - config_name: videos |
| data_files: |
| - split: videos |
| path: metadata/videos.parquet |
| - split: sample_videos |
| path: samples/metadata/videos.parquet |
| --- |
| |
| # MEV: A Multi-Event Video Dataset for Long-Take Generation |
|
|
| <p align="center"> |
| <a href="https://openreview.net/forum?id=blH6L8WmTv"><img src="https://img.shields.io/badge/Paper-OpenReview-B31B1B?style=flat&labelColor=344054" height="20" alt="Paper · OpenReview"></a> |
| <a href="https://github.com/SoftPointer/MEV"><img src="https://img.shields.io/badge/GitHub-Code-181717?style=flat&labelColor=344054&logo=github&logoColor=white" height="20" alt="GitHub · Code"></a> |
| <a href="https://mev-dataset.github.io/"><img src="https://img.shields.io/badge/Project-Page-2563EB?style=flat&labelColor=344054" height="20" alt="Project Page"></a> |
| <a href="#citation"><img src="https://img.shields.io/badge/Citation-BibTeX-BE185D?style=flat&labelColor=344054" height="20" alt="Citation · BibTeX"></a> |
| <a href="#citation"><img src="https://img.shields.io/badge/NeurIPS-2026-7C3AED?style=flat&labelColor=344054" height="20" alt="NeurIPS 2026"></a> |
| </p> |
|
|
| MEV is a dataset for long-take multi-event video generation, with 8k real-world |
| videos and 25k temporally grounded events. It provides Global and Event |
| annotations, including multi-granularity captions, camera descriptions, semantic |
| attributes, and six VBench quality scores. |
|
|
| The canonical nested annotation file is `annotations/mev.json`. The primary |
| machine-readable table is `metadata/events.parquet`, where each row corresponds |
| to one event segment. |
|
|
| ## Repository Layout |
|
|
| - `annotations/mev.json`: canonical full annotation file. |
| - `metadata/events.parquet`: full event-level table. |
| - `metadata/events.csv` and `mev.csv`: CSV mirrors for inspection. |
| - `metadata/videos.parquet`: UUID-level index. |
| - `raw/720p/raw-*.tar`: 8,016 original videos, stored as `<uuid>.mp4`. |
| - `raw/1080p/raw-*.tar`: 1,896 optional higher-resolution originals. |
| - `videos/mev-*.tar`: full video segment tar shards. Tar members preserve the original mp4 filenames. |
| - `samples/`: reviewer-friendly sample subset with matching annotation, metadata, and tar shard(s). |
|
|
| ## Loading Metadata |
|
|
| ```python |
| from datasets import load_dataset |
| |
| events = load_dataset("MultiEventVideo/MEV", split="events") |
| videos = load_dataset("MultiEventVideo/MEV", "videos", split="videos") |
| sample_events = load_dataset("MultiEventVideo/MEV", split="sample_events") |
| ``` |
|
|
| The default `events` configuration contains the `events` and `sample_events` |
| splits. The `videos` configuration contains `videos` and `sample_videos`. |
| These are table and inspection-subset names, not experimental train/test splits. |
|
|
| Each event row includes `shard_path`, `tar_member`, and `media_ref`. For example: |
|
|
| ```text |
| videos/mev-000000.tar::<original-segment-filename>.mp4 |
| ``` |
|
|
| `has_cooking` is a boolean indicating food or beverage preparation, or active |
| cooking/heating, during at least part of the event. |
|
|
| ## Download and Extract Videos |
|
|
| Loading the metadata with `load_dataset` does not download the video archives. |
| The following commands use a macOS or Linux shell. |
|
|
| ### Download the dataset |
|
|
| Install the [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli) |
| and download the repository to a local `MEV` directory: |
|
|
| ```bash |
| python -m pip install -U huggingface_hub |
| hf download MultiEventVideo/MEV --repo-type dataset --local-dir ./MEV |
| cd MEV |
| ``` |
|
|
| The complete download is approximately 227 GB. Run the commands below from this |
| `MEV` directory. Individual archives can also be downloaded from the repository's |
| Files tab, preserving the same directory layout. |
|
|
| ### Extract the original and event videos |
|
|
| The `.tar` archives contain MP4 files and have no additional gzip compression. |
| Create an `extracted/` subdirectory within each archive directory and extract the |
| videos there. The tar files remain in their existing locations: |
|
|
| ```bash |
| for directory in raw/720p raw/1080p videos; do |
| mkdir -p "$directory/extracted" |
| for archive in "$directory"/*.tar; do |
| tar -xf "$archive" -C "$directory/extracted" |
| done |
| done |
| ``` |
|
|
| After running these commands, the directories contain: |
|
|
| ```text |
| raw/720p/ |
| raw-*.tar |
| extracted/<uuid>.mp4 # 8,016 primary original videos |
| raw/1080p/ |
| raw-*.tar |
| extracted/<uuid>.mp4 # 1,896 available alternate originals |
| videos/ |
| mev-*.tar |
| extracted/<original-event-filename>.mp4 # 25,262 event videos |
| ``` |
|
|
| Here, `raw/` holds original videos, while `videos/` holds Event videos. |
|
|
| Open the extracted MP4 files in a video player. Original filenames are preserved: |
| match raw videos by `uuid` and event videos by each annotation's `filename`. |
| The 1080p directory contains alternate originals, not additional dataset UUIDs. |
| Keeping the archives and all extracted full-data videos uses approximately 450 GB. |
|
|
| To inspect a single archive before extracting it: |
|
|
| ```bash |
| tar -tf videos/mev-000000.tar |
| ``` |
|
|
| Videos can also be read directly from their tar archives using the Python example |
| under **Original video access**, without extracting the complete archives. |
|
|
| ## Sample Subset |
|
|
| The `samples/` directory contains a smaller subset intended for reviewer |
| inspection. It is drawn from the full MEV release at the UUID level; all events |
| from selected UUIDs are preserved. |
|
|
| Selection includes all videos with saved human-review records from the web |
| annotation interface that are present in this release: 226 original |
| videos and 721 events. Annotations are copied from the current full |
| dataset. Selection is at the video level; it does not imply that every field was |
| individually reviewed. `samples/uuids.txt` records the exact membership. |
| `samples/raw/720p/` contains the original videos, and `samples/videos/` contains |
| their event videos. This is an inspection subset, not a random population sample |
| or the experimental train/test split. |
|
|
| ## License |
|
|
| This repository uses `mixed-third-party-licenses`. |
|
|
| Original Mixkit, YouTube, and other third-party videos remain subject to their respective platform terms and rights-holder licenses. The dataset authors do not claim ownership of third-party video assets and do not re-license them under CC BY, MIT, Apache, or any other open-source license. |
|
|
| The official released video package is directly downloadable for research, |
| evaluation, and model training, subject to applicable source-specific terms |
| described in `LICENSE`. Optional restricted or premium source variants are not |
| automatically part of the public package. Preserve available source attribution |
| and provenance. The repository's existing `LICENSE` is authoritative. |
|
|
| Annotations, labels, splits, benchmark metadata, and other author-created materials are released under the Creative Commons Attribution 4.0 International License, CC BY 4.0. |
|
|
| See the `LICENSE` file for full details. |
|
|
| ## Original video access |
|
|
| The dataset contains 8,016 original videos and 25,262 events. |
|
|
| The Global table (`metadata/videos.parquet`) includes `raw_720p_shard_path`, |
| `raw_720p_tar_member`, `raw_720p_media_ref`, `raw_720p_bytes`, and `raw_720p_sha256`. |
| The full table also links available alternate originals with the corresponding |
| `raw_1080p_*` columns. Empty alternative references indicate that the table does |
| not provide that variant. The sample supplies the primary original videos. |
| Resolution directory names preserve the source storage groups; actual media |
| dimensions can vary. Every tar preserves the original MP4 bytes and filenames. |
|
|
| All archives are uncompressed tar shards, each at most 5 GiB. To read an |
| original video and its first event directly from the downloaded archives, |
| install the table-reading dependencies: |
|
|
| ```bash |
| python -m pip install pandas pyarrow |
| ``` |
|
|
| Then run this Python example from the downloaded `MEV` directory: |
|
|
| ```python |
| from pathlib import Path |
| import tarfile |
| import pandas as pd |
| |
| root = Path(".") |
| videos = pd.read_parquet(root / "metadata/videos.parquet") |
| events = pd.read_parquet(root / "metadata/events.parquet") |
| video = videos.iloc[0] |
| event = events[events.uuid == video.uuid].iloc[0] |
| |
| def read_media(reference): |
| archive, member = reference.split("::", 1) |
| with tarfile.open(root / archive) as tar: |
| return tar.extractfile(member).read() |
| |
| raw_bytes = read_media(video.raw_720p_media_ref) |
| event_bytes = read_media(event.media_ref) |
| ``` |
|
|
| Join the Global and Event tables on `uuid`. Each Event row stores its original |
| video timestamps, an event ID starting at 1, its tar reference, byte size, and |
| SHA-256. The HF table split names identify data views, not experimental train/test |
| assignments. |
|
|
| ## Citation |
|
|
| If you use MEV in your research, please cite: |
|
|
| ```bibtex |
| @misc{mev2026, |
| title = {MEV: A Multi-Event Video Dataset for Long-Take Generation}, |
| author = {Zhu, Peiyuan and Xie, Shaoan and Shen, Yifan and Tian, Wen and |
| Li, Zijian and Chen, Guangyi and Zhang, Kun}, |
| year = {2026}, |
| url = {https://mev-dataset.github.io/} |
| } |
| ``` |
|
|
