---
license: cc-by-4.0
pretty_name: video2sim captures
language:
  - en
task_categories:
  - video-classification
  - image-to-3d
tags:
  - video
  - 3d-reconstruction
  - robotics
  - simulation
  - benchmark
size_categories:
  - n<1K
---

# video2sim captures

Short handheld videos of workspaces, captured as input for the video2sim pipeline
(video → reconstruction → segmentation → shape → physics → simulation assets).

## Contents

- `scenes/s01–s24/`: 24 scenes, each with:
  - `video_a.mp4` — orbit around the table
  - `video_b.mp4` — rough side view
  - `alt_*/` — extra takes (`alt_lighting`, `alt_path`, `alt_closeup`,
    `glass_bottle_close`)
- `scenes/thumbnails/`, `scenes/thumbnails_lowres/`: preview images
  (1920×1080 and 640×360)

Clips are `.mp4`, 5–65 seconds each. Scenes s06, s14 and s24 are
video_b-only (plus two `alt_path` takes each).

## Capture protocol

- Device: iPhone 14
- Resolution: 1920×1080
- Frame rate: 30 fps
- Camera motion: VideoA is an orbit around the table, VideoB a rough side view
- Lighting: mostly diffuse room light (optimal conditions); some scenes use natural light

## Privacy and consent

Scenes are clean for the most part. One background document still needs a double-check
before public release.

## Intended use

Research and benchmarking of video-to-simulation pipelines.

## Citation

```bibtex
@dataset{korbmacher2026video2sim,
  author    = {Korbmacher, Tom Korbmacher, Tom},
  title     = {video2sim captures},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/TomKrb/video2sim-captures}
}
```