SolarWM-Data

SolarWM-Data is a reusable video-data foundation for camera-conditioned world-model research. The main Hugging Face repository publishes portable release controls, licenses, deterministic test indexes, and directly readable format examples. It also contains the SolarWM-Data-Annotation/ reconstruction package. The full raw video and preencoded latent payloads are distributed separately because of their size and upstream terms.

Main repository: junchaoh-cs/SolarWM-Data

SolarWM-Data/
  README.md
  SolarWM-Data-Annotation/
  releases-v1/
    release.json
    checksums.jsonl.gz
    recipes/
      clean-81f/
      clean-153f/
      clean-158f-h3/
      clean-957f/
    test-set/
    example/
    licenses/
    raw-wds/      # obtained separately when a raw example needs it
    latent-wds/   # separately published, backend-specific generations

release.json and checksums.jsonl.gz describe the complete logical release across its distribution repositories. Their presence in the main repository does not mean that all raw and latent payloads are stored in that repository. Recipe rows use paths relative to releases-v1/, so separately downloaded payloads can be placed into the same local tree.

Download the main repository

python -m pip install --upgrade huggingface_hub
hf download junchaoh-cs/SolarWM-Data \
  --repo-type dataset \
  --exclude "SolarWM-Data-Annotation/**" \
  --local-dir /path/to/SolarWM-Data

The small releases-v1/example/ archives support schema inspection and reader or preencoding smokes. They are not a training corpus. Remove the --exclude option to download the Annotation package too, or use --include "SolarWM-Data-Annotation/**" to download only that package.

Add the payload needed by your run

There are three routes:

1. Reconstruct raw-WDS from annotations. The SolarWM-Data-Annotation/ directory in this repository contains annotations, public source identities, and the reconstruction tools. Its three *-clean owners also include the processed videos, so they restore without a model or GPU. For the other 11 owners, users acquire the original videos under their respective terms and follow that directory's README to rebuild raw-wds/.
2. Request raw-WDS access. Use the Raw-WDS Access entry on the SolarWM project page.
3. Download preencoded data. Every Wan, LTX, and MiniMax-H3 latent generation will have a separate dataset repository. Links will be added to the SOLAR-WM code repository's docs/data-access.md as uploads complete.

Preserve raw payloads under releases-v1/raw-wds/ and latent payloads under releases-v1/latent-wds/<generation>/. The selected SOLAR-WM example's train_index, index, and test_index fields state exactly which payloads it needs.

Complete annotated corpus

The 14-source raw corpus contains 1,425,694 samples: 471,798 high, 404,795 xhigh, and 549,101 rejected. Rejected shards are part of the release. Every sample retains kept, kept_tier, reject_reasons, and the available camera, motion, quality, scene, and VLM measurements.

Source preprocessing and training-mixture construction are separate. Users can change thresholds, tier policies, sampling ratios, and source weights without rerunning video decoding, camera estimation, VMAF, UniMatch, DOVER, saturation, scene-cut, or VLM processing.

The source directories are abot, dl3dv-10s, dl3dv-60s, mind, miradata, miradata-clean, multicamvideo, omniworld, realcam_vid, sekai_game, sekai_walking, sekai_walking-clean, spatialvid, and spatialvid-clean. Each directory contains tiered WebDataset shards, meta.jsonl, and complete tier/sample indexes.

Preencoded data

latent-wds/ provides reader-ready generations for Wan 2.2 TI2V-5B at 81f, 153f, and 957f with published 480P/720P variants; Wan 2.2 I2V-A14B at 81f, 153f, and 957f with the published 480P/720P variants; MiniMax-H3 at 158f/768P; and LTX-2.5 video-only at 153f and 953f. Tensor member manifests declare their solarwm_* schema, source identity, shape, dtype, and camera contract.

Camera trajectories and intrinsics are included in each record and are ready for the corresponding SolarWM reader.

Recipes and evaluation

Recipe indexes use relative object keys so the same controls work with a local copy or with bucket streaming. Evaluation selects a deterministic subset from the matching recipe test-index.jsonl.gz using sample_count and selection_seed.

test-set/ is a logical view of canonical primary raw shards. It preserves selection rank, split identity, and minimum-frame requirements without storing a second copy of each video.

example/ contains one raw representative from each annotation tier and one representative of every declared release latent generation. Each example record names the release object from which it was derived.

Local use

Set both SOLAR-WM paths to the same local release root. A local copy may live at any absolute path:

data:
  index_root: /path/to/SolarWM-Data/releases-v1
  transport:
    kind: local
    root: /path/to/SolarWM-Data/releases-v1

Indexes resolve shard paths relative to that root. The checksum catalog is available when a complete release-integrity check is needed.

Licenses and citations

Media and annotations retain their upstream terms. There is no blanket license that replaces source-dataset restrictions. Read releases-v1/licenses/source-registry.json and the linked upstream terms before use, redistribution, or creation of derived data. Model weights are not part of this data release.