| --- |
| pretty_name: VideoVAE Datasets |
| task_categories: |
| - video-generation |
| --- |
| |
| # VideoVAE-Datasets |
|
|
| Quality-filtered real-world videos for training video VAE decoders. |
| **Final training set: 84,335 videos** (see `training-metadata/`). |
|
|
| ```text |
| training-metadata/ final qualified + deduplicated video list, curation results <- start here |
| stage_0/ pilot set: every OpenViD-HD video in part_48..part_55, unfiltered (local videos only) |
| OpenViD-HD/ |
| videos/{min132,min121-131,min81-120}/part-NNNN/shard-NNN.tar |
| metadata/quality/part_N.json, index.json |
| metadata/captions/OpenVidHD.csv, source.json original OpenVidHD captions (join on video file name) |
| latents/wan2.1/chunks-33frames/ Wan2.1 VAE latents (33-frame sections) + manifests/ + README.md |
| UltraVideo/ |
| videos/{min132,min121-131,min81-120}/clips_short_960/shard-NNN.tar |
| videos/{min132,min121-131,min81-120}/clips_short_1920/shard-NNN.tar 1920x1080 versions, quality-passed only |
| metadata/quality/clips_short_960.json, clips_short_1920.json, index.json |
| Miradata/ |
| videos/min132/miradata_v1/shard-NNN.tar |
| metadata/quality/miradata_v1.json, index.json |
| ``` |
|
|
| | Dataset | Source | Qualified | Final (after dedup) | |
| |---|---|---:|---:| |
| | OpenViD-HD | [nkp37/OpenVid-1M](https://huggingface.co/datasets/nkp37/OpenVid-1M), OpenVidHD parts | 78,583 | 72,982 | |
| | UltraVideo | [APRIL-AIGC/UltraVideo](https://huggingface.co/datasets/APRIL-AIGC/UltraVideo), clips_short_960 | 11,143 | 9,698 | |
| | MiraData | [MiraData v1](https://github.com/mira-space/MiraData), real-world clips | 1,868 | 1,655 | |
|
|
| - `videos/` folders are frame-count ranges (original MP4 bytes, no trimming or re-encoding). |
| Video TARs contain every qualified video; MiraData TARs also contain videos that failed |
| quality. Select training videos with `training-metadata/train.jsonl`. |
| - `metadata/quality/*.json` hold per-video CPU quality measurements and gate results for |
| every source video, passed or not. OpenViD-HD quality covers part_1, part_2 and |
| part_10..part_60; quality-passed videos of part_48..part_55 are included in the TARs. |
| - UltraVideo `clips_short_1920` holds the same clips as `clips_short_960` at 1920x1080, |
| quality-checked with the same gates; it is not part of the final training set. Passed rows |
| in `clips_short_1920.json` carry `hf_archive` / `hf_archive_member`. |
| - All paths in metadata are relative to the dataset root (e.g. `OpenViD-HD/videos/part_48/x.mp4` |
| after extracting TARs as `<root>/<Dataset>/<archive member>`). |
| - Download everything except latents: |
| `hf download mingyang-wu/VideoVAE-Datasets --repo-type dataset --exclude "*/latents/*" --local-dir VideoVAE-Datasets` |
|
|
| ## evaluation/ |
|
|
| Reconstruction evaluation sets, one TAR each. Extract with `tar -xf <archive> -C <root>` |
| to get `<root>/<Dataset>/...`; checksums are in `evaluation/SHA256SUMS`. |
|
|
| | Archive | Contents | Source | |
| |---|---|---| |
| | `Inter4K.tar` | 1,000 Inter4K MP4s at `Inter4K/60fps/UHD/<id>.mp4`, original files unmodified (3840×2160, ~60 fps, ~5 s) | [Inter4K](https://github.com/alexandrosstergiou/Inter4K), Alexandros Stergiou and Ronald Poppe; fetched from the Hugging Face mirror [Shilin-LU/Inter4k](https://huggingface.co/datasets/Shilin-LU/Inter4k) | |
| | `WebVid10M-val-1k.tar` | 1,000 WebVid-10M validation videos | WebVid-10M | |
| | `Large-Motion-100-recreated.tar` | 100 high-motion clips (80 WebVid + 20 Inter4K) chosen by optical flow; a recreation, not the original unreleased split | built in this project from the two sets above | |
| | `MPI-Sintel.tar` | Official MPI-Sintel frames with 5 training scenes held out as a custom validation split | [MPI-Sintel](http://sintel.is.tue.mpg.de/) | |
|
|
| **Inter4K license.** Inter4K is © 2021 Alexandros Stergiou and is licensed under |
| [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) (see the original |
| [licence.txt](https://github.com/alexandrosstergiou/Inter4K/blob/main/licence.txt)): non-commercial |
| use only, with attribution, and adaptations under the same license. The files here are |
| redistributed unmodified. The same terms apply to the 20 Inter4K clips in |
| `Large-Motion-100-recreated.tar`. Cite: |
|
|
| ```bibtex |
| @article{stergiou2021adapool, |
| title = {AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling}, |
| author = {Stergiou, Alexandros and Poppe, Ronald}, |
| journal = {arXiv preprint}, |
| year = {2021} |
| } |
| ``` |
|
|
| The other evaluation sets keep the terms of their original sources. |
|
|
