This repository contains training-video shards prepared for VideoVAE experiments. - Videos available on the packaging host: 27,351. - Each shard contains videos/partN/.mp4 and an internal manifest.jsonl. - Global manifests are under OpenViD-HD/metadata/manifests/videos-min132/. The 81--131-frame expansion is intentionally not included in this release because the complete quality-metric table needed to apply the same gates was unavailable when this subset was packaged. See OpenViD-HD/README.md for the organized videos, VAE latents, and current >=121-frame qualified selection. The older description above documents the original release. See UltraVideo/README.md for the metadata-first…
SAVRN Model Hub · Datasets by Task
Video Generation Datasets
2 open-weight video generation datasets in the SAVRN Model Hub, with Shengxiang Ji and MingyangWu publishing the most.
2Datasets
2Publishers
2Licenses
Most Downloaded
| Dataset | Publisher | License | Monthly downloads |
|---|---|---|---|
| VideoVAE-Datasets | MingyangWu | Not stated | 237 |
| LIFT-Vista | Shengxiang Ji | cc-by-nc-sa-4.0 | — |
Licenses
| License | Datasets | Commercial use |
|---|---|---|
| not stated | 1 | Not stated |
| cc-by-nc-sa-4.0 | 1 | Not without separate permission |
Who Publishes Them
| Publisher | Datasets |
|---|---|
| Shengxiang Ji | 1 |
| MingyangWu | 1 |
All 2 Datasets
LIFT-Vista is a dataset with large camera viewpoint changes and joint camera-layout annotations. Every clip has 81 frames at 16 fps (about 5 s) at the native resolution of its source video (98% are 1280×720), encoded with H.264. The release is about 413 GB, of which 407 GB are videos. Videos and annotations are stored as tar shards in tars/ (about 4 GB per video shard). Extracting them in the dataset root restores the videos/ and annotations/ directories that the CSV paths point to (413 GB in total): camlayout.csv only needs the camlayout shards (179 GB): is SpatialVID, Sekai or RealEstate10K, is the id of the video in the source dataset, and is the window index w of the 81-frame window…