--- license: cc-by-4.0 pretty_name: "Syn4D windows with ground-truth Track4D caches (Track4DGEN v3)" viewer: false tags: - 4d - video - synthetic - point-tracking - depth - 3d-bounding-boxes size_categories: - 1K.tar syn4d_tracks///{clip.mp4, track/...} SHA256SUMS every file of this repository LICENSE LICENSES/ THIRD_PARTY_NOTICES.md sequence_to_asset_mapping.csv Syn4D's, unchanged ``` Download and extract every shard into one folder; the index's paths are relative to it: ```bash hf download HugMinjun/Syn4D-Track4D-v3 --repo-type dataset --local-dir Syn4D-Track4D-v3 cd Syn4D-Track4D-v3 && sha256sum -c SHA256SUMS && for t in shards/*.tar; do tar -xf "$t"; done ``` Track4DGEN's `tools/syn4d/hf_download.py` does the same scene by scene (checksums, extraction, deleting each tar). ### Index rows (`index_b.jsonl`) ```json {"path": "syn4d_tracks/arena/seq_000000_0_w0_n129/clip.mp4", "id": "syn4d:arena:seq_000000_0:w0:n129", "source_id": "syn4d:arena:seq_000000_0:w0:n129", "caption": "Three individuals are on a wooden platform ...", "split": "train", "frames": 129, "tracking_frames": 129, "fps": 15.0, "tracks": "syn4d_tracks/arena/seq_000000_0_w0_n129/track", "metric_reference": {"scale": 1.0}, "gravity_up_world": [0.002167, -0.680545, -0.732703]} ``` - `id`: `syn4d:::w:n`; `` / `` are Syn4D's names. - `gravity_up_world`: the world's up (Unreal's +Z) in the window's coordinate frame, a unit vector, from Syn4D's camera CSVs. - `metric_reference: {"scale": 1.0}`: the caches are already in metres. ### Window folder (`syn4d_tracks///`) - `clip.mp4`: the window's renders, H.264, 1280 × 720, 15 fps (training crops the centre 704 × 1280). - `track/compact.npz` (T frames, N tracked instances, Q query points): | Array | Shape, type | Meaning | |---|---|---| | `cam_R`, `cam_t` | (T, 3, 3), (T, 3) float32 | camera-to-world; world = the window's first camera, OpenCV axes, metres | | `intrinsics` | (T, 3, 3) float32 | at the 308 × 560 tracker resolution (of the 704 × 1280 crop) | | `depth16` | (T, 308, 560) float16 | z-depth in metres, NaN where invalid | | `all_masks`, `query_masks` | (T, 704, 1280), (704, 1280) uint8 | 0 background, 1..N tracked moving instances, 200 moving pixels that are not tracked (objects appearing later, pixels that are neither environment nor an object) | | `fg_prob` | (T, 308, 560) uint8 | foreground probability | | `traj`, `conf`, `vis_logits` | (T, Q, 3), (T, Q), (T, Q) float32 | world trajectories of the query points, their confidence and visibility | | `query_xyz`, `query_uv`, `query_instance` | (Q, 3), (Q, 2), (Q,) | the queries in the first frame and their instance | | `pose`, `T_world_from_canon`, `corners`, `half`, `scale`, `pose_valid` | (N, T, ...) | per-frame 3D boxes of the tracked instances | | `box0_center`, `box0_R`, `box0_half`, `instance_ids` | (N, ...) | first-frame boxes, instance ids | - `track/box_refit.{npz,json}`: per-frame boxes re-fitted from the masks and the depth (median size); Track4DGEN's cache loader applies them over `compact.npz`'s boxes. - `track/result.json`: per-instance metadata and the Syn4D source (`syn4d`: scene, sequence, frame range, groups); `track/observations.json`, `track/sampling.json`: Track4DGEN's observation and sampling metadata. ## How it was made From Syn4D V1 (stride-1 bundle: frames, depth, masks, cameras and tracking records; stride-5 bundle: the window index, captions and the camera CSVs for the gravity), on CPUs only (Track4DGEN `tools/syn4d`, branch `datasets/syn4d`): 1. Windows of 129 / 97 / 65 frames at 15 fps over each sequence. 2. Cameras: Syn4D's CSV rows (Unreal centimetres, left-handed) to OpenCV camera-to-world in metres, relative to the window's first camera. Depth: EXR depth ÷ 100. 3. Instances: one per Syn4D mesh group (a person's body and clothing are one instance). Since every Syn4D object is animated, an object counts as static only if the 90th percentile of its faces' displacement stays under 1 cm; moving objects visible in the first frame are tracked, the others get id 200. 4. Trajectories: each query's first-frame mesh face is found again in every frame through Syn4D's tracking records. 5. Boxes: Track4D's fitting code, then re-fitted per frame from masks and depth. 6. Captions: the sequence's Syn4D caption where the scene ships them, otherwise Qwen3-VL-8B-Instruct (`0c351dd`) over 8 frames of the sequence. The renders, depth, masks, cameras and tracking records are Syn4D's; this dataset changes their frame rate, crops, units and coordinate frames, and adds the caches and the generated captions. ## License and third-party assets Released under **CC BY 4.0**, like Syn4D. Syn4D's `LICENSE`, `LICENSES/`, `THIRD_PARTY_NOTICES.md` and `sequence_to_asset_mapping.csv` are included unchanged and apply to this dataset as they do to Syn4D: - **BEDLAM2**: every sequence of these 29 scenes depends on BEDLAM2 bodies (`asset_type` `bedlam2_body` in the mapping). As for Syn4D, no BEDLAM2 data is redistributed here, and you must obtain BEDLAM2 from its official source and agree to the BEDLAM2 license before using BEDLAM2-dependent sequences. - Fab / Unreal scenes (Fab Standard License), Objaverse objects (ODC-By 1.0, each object under its own license), Google Scanned Objects (CC BY 4.0): see `THIRD_PARTY_NOTICES.md`. No rights to third-party assets are granted.