---
license: other
tags: [4d-reconstruction, video-to-4d, sam-3d]
---

# ff4d-sam3d prepped training data (motion324 + syn4d)

> **STATUS: upload complete (2026-09-07 23:01 UTC). Check `COMPLETE.txt` for the per-stream entry counts.**
> Files appear a few GB at a time, stream by stream. `pointmaps` is the largest stream and lands
> last for each root. Check the file list for what is already complete; a `__NNN.tar` that is
> present is complete (each is committed only after a successful upload).

Prepped training samples for ff4d-sam3d — video-to-4D on the SAM-3D Objects backbone. Each sample
is **one scene × object × motion**; views are augmentation and share the SS/SLat latents, differing
only in the layout target and the input conditioning.

**Derived data.** These are artifacts (renders, pointmaps, encoded latents, layout targets) computed
from third-party sources — see *Sources* below. Use of this data is bounded by those sources'
licenses; cite them, not just this repo.

## Sources

| root | derived from | samples |
| --- | --- | --- |
| `ff4d_sam3d_m324_scale4k` | [River-Chen/Motion324](https://huggingface.co/datasets/River-Chen/Motion324) train shards `part_0001`–`part_0004` | ~4,000 objects |
| `ff4d_sam3d_motion324` | Motion324 (earlier 500-object prep, 13-camera rig) | 500 objects |
| `ff4d_sam3d_syn4d_full_objscale` | syn4d corpus | 2,678 samples (geometry only, no SLat) |

Objects in `scripts/prepare/m324_eval_holdout_shas.txt` are excluded — they are the evaluation
holdout and must not appear in training data.

## Streams

```
layout_targets/<sha>.npz                              per-frame (R, t, s) + rotation-6d tokens
layout_targets_metric/<sha>.npz                       per-view metric layout
renders_cond_pm/<sha>/<view>/%04d.png                 full-frame RGBA conditioning renders
renders_cond_pm/<sha>/cameras.npz                     extrinsics / intrinsics / cam names
pointmaps/<sha>/<view>/%04d.npy                       512x512x3 float16, NaN off-object
ss_latents_video_canon/sam3d_ss_enc_16l8/<sha>.npz    mean (F,8,16,16,16) + per-frame center, scale
slat_latents_video_canon/sam3d_slat_enc_8l8/<sha>.npz sparse coords (N,4) + feats (N,8)
```

Files are named by sha and disjoint across shards, so merging two shards is a plain copy.

## Recipe

`scripts/prepare/prep_motion324.sh`, 8 frames, steps `rigid cond canon slat pointmap` (no `align`),
encoders `sam3d_ss_enc_16l8` / `sam3d_slat_enc_8l8`, `checkpoints/hf`. Objects from `part_0001`–
`part_0002` were prepped with 4 yaws (`0 90 180 270`); later objects with a single yaw (`270`), since
views share the latents and only multiply the conditioning streams.

## Packaging

Streams are uploaded as gzip-compressed tars (`<root>__<stream>__NNN.tar.gz`) because the
untarred roots are 100k+ small files. Pointmaps compress ~17x (float16, mostly NaN off-object).
Extract with `tar xzf <file> -C data/<root>/<stream>/`.