---
license: cc-by-4.0
pretty_name: "Syn4D Track4DGEN v3 training caches (conditions, target latents, text embeddings)"
viewer: false
tags:
- 4d
- video
- synthetic
- point-tracking
- 3d-bounding-boxes
---

# Syn4D Track4DGEN v3 training caches

The GPU stage's outputs for **[HugMinjun/Syn4D-Track4D-v3](https://huggingface.co/datasets/HugMinjun/Syn4D-Track4D-v3)**:
memory / control conditions, target latents and caption embeddings for SanaTrack training, made from that dataset's
5,817 windows of [Syn4D](https://huggingface.co/datasets/Syn4D/Syn4D) V1 (revision `bb08d13f`).

This is a derivative of Syn4D, not an official Syn4D release. Please cite Syn4D
([arXiv:2605.05207](https://arxiv.org/abs/2605.05207), [project page](https://jzr99.github.io/Syn4D/)) when you use it.

## Contents

| | |
|---|---|
| Pairs | 12,051 memory → target pairs of 33 frames at 15 fps (`manifests/pairs.jsonl`) |
| Clips | 5,682 windows |
| Conditions | 61,374 files: per clip, `pairs/conditions.zip` with each pair's memory latent, control latents, cameras and object paths |
| Target latents | 12,051 files: SANA-WM LTX-2 VAE latents `[128, 5, 22, 40]` of the 33-frame target chunk at 704 × 1280; the first temporal slice is the condition-image latent |
| Text | 5,683 files: Gemma-2-2B-it caption embeddings `[1, 300, 2304]` through the SANA-WM text pipeline, plus `negative.safetensors` |
| Storage | bf16 latents and embeddings (no int8 quantization) |
| Size | 38.4 GiB in uncompressed tar shards |

The condition images are not duplicated here. They are decoded from the windows' `clip.mp4`, which you get from
HugMinjun/Syn4D-Track4D-v3.

## Layout

```
manifests/pairs.jsonl          the training manifest (one row per pair)
manifests/loader.json          SanaTrack loader entry (paths of the producing server, see below)
manifests/plan.json            the export plan
manifests/selection_report.json, index_b.jsonl   instance selection report and the GPU stage's index
shards/conditions-<h>.tar      v3/conditions/clips/<h>*/...   (h = first hex digit of the clip directory)
shards/targets-<h>.tar         v3/targets/<h>*/...
shards/text.tar                v3/text/...
SHA256SUMS
```

Tar members are relative to the Syn4D root. Extract every shard into the same root as the CPU release:

```bash
ROOT=/data/Syn4D
# 1. clips: the CPU release (tools/syn4d/hf_download.py in Track4DGEN), giving $ROOT/syn4d_tracks/*/*/clip.mp4
# 2. this release
hf download HugMinjun/Syn4D-Track4D-v3-training --repo-type dataset --local-dir "$ROOT/training-release"
(cd "$ROOT/training-release" && sha256sum -c SHA256SUMS)
for t in "$ROOT"/training-release/shards/*.tar; do tar -xf "$t" -C "$ROOT"; done
cp "$ROOT"/training-release/manifests/pairs.jsonl "$ROOT"/v3/conditions/pairs.jsonl
# 3. the paths in pairs.jsonl / loader.json are the producing server's (/workspace/dataset/Syn4D): map them
python scripts/prepare_datasets.py --out configs/main --dataset "$ROOT"/training-release/manifests/loader.json \
  --map /workspace/dataset/Syn4D="$ROOT"
```

## How it was made

Track4DGEN `tools/syn4d/run_gpu.sh` (branch `datasets/syn4d`, commit `b905d1c`), steps 2–5 of `tools/syn4d/GPU_GUIDE.md`:

1. Export: memory / control conditions of every pair kept by the instance selection (`dynamic_first_v3`, boxes
   `gravity_median_box_v1` on Syn4D's ground-truth gravity), `scripts/run_v3_parallel.py --windows --storage-format bf16`.
2. Target latents: `tools/sanatrack/build_pair_targets.py` (SANA-WM bidirectional VAE, `e96271d`).
3. Text: `tools/sanatrack/build_text_cache.py` (gemma-2-2b-it, `569d9809`).
4. Completeness: every pair of `pairs.jsonl` has its target latent and its clip's text embedding.

Produced on 4 × TITAN RTX (Turing, no native bf16). Two changes to `b905d1c` were used:

- The VAE and Gemma computed in **fp32** (`T4D_COMPUTE_DTYPE=fp32` in `ltx2_vae.py` and `tools/sanatrack/sanatrack/sana.py`);
  outputs are cast to bf16 for storage as usual. Values can differ slightly from a bf16-compute run.
- Gravity vectors are passed to the tracking worker in positional notation (`scripts/v3_track_worker.py`): values such as
  `-8.2e-05` or `-0.0` were otherwise parsed as command-line options and stopped the export. The values are unchanged.

## License and third-party assets

Released under **CC BY 4.0**, like Syn4D. Syn4D's `LICENSE`, `LICENSES/` and `THIRD_PARTY_NOTICES.md` are included
unchanged and apply as they do to Syn4D. Every sequence depends on BEDLAM2 bodies: no BEDLAM2 data is redistributed
here, and you must obtain BEDLAM2 from its official source and agree to its license before using these sequences.
No rights to third-party assets (Fab / Unreal scenes, Objaverse objects, Google Scanned Objects) are granted.