---
pretty_name: SemanticVLA TraceX 240K DROID
tags:
- robotics
- lerobot
- droid
- franka
- semanticvla
- tracex
- lerobot-v3
license: other
configs:
- config_name: default
  data_files:
  - split: train
    path: data/**/*.parquet
---

# SemanticVLA TraceX 240K · DROID

> 🎉 **Accepted to [CVPR 2026](https://cvpr.thecvf.com/virtual/2026/poster/39352).**<br>
> ✍️ Fei Ni¹, Zhuo Chen², Yifu Yuan³, Zibin Dong³, Xianze Yao³, Shan Luo², Jianye Hao³, Jiankang Deng¹†, Stefanos Zafeiriou¹†<br>
> 🏫 ¹Imperial College London &nbsp;&nbsp; ²King's College London &nbsp;&nbsp; ³Tianjin University<br>
> ✉️ Primary contact: [f.ni@imperial.ac.uk](mailto:f.ni@imperial.ac.uk)

The **DROID** component of [**TraceX-240K**](https://hf.co/collections/spikefly/semanticvla-datasets) — the trace-annotated trajectory corpus introduced in **SemanticVLA**. This package is a LeRobot v3.0 repack of DROID · Franka · Open-X-Embodiment DROID v1.0.1 with **dense per-frame end-effector trace labels** stored directly in every frame row.

> 📚 **Code · checkpoints · paper:** https://github.com/Fei-Ni/SemanticVLA_Offcial

## 🎬 Sample trace overlays

Each clip shows the orange trace label (per-frame gripper position) overlaid on the original episode camera feed.

<table>
  <tr>
    <td><img src="assets/trace_overlays/ep_005699.gif" width="200" alt="episode 5699"></td>
    <td><img src="assets/trace_overlays/ep_011349.gif" width="200" alt="episode 11349"></td>
    <td><img src="assets/trace_overlays/ep_033979.gif" width="200" alt="episode 33979"></td>
    <td><img src="assets/trace_overlays/ep_039547.gif" width="200" alt="episode 39547"></td>
  </tr>
  <tr>
    <td align="center"><sub>episode 5699</sub></td><td align="center"><sub>episode 11349</sub></td><td align="center"><sub>episode 33979</sub></td><td align="center"><sub>episode 39547</sub></td>
  </tr>
</table>

## 🧭 Trace label schema

Dense per-frame end-effector position columns, stored directly in every frame row:

- `trace.x` — `float32[1]`, normalized image-space x coordinate on a `[0, 100]` scale.
- `trace.y` — `float32[1]`, normalized image-space y coordinate on a `[0, 100]` scale.

`(0, 0)` is the top-left corner of the frame, `(100, 100)` the bottom-right.

**DROID per-episode camera:** unlike Bridge / Fractal / BC-Z (single fixed camera), DROID's trace was projected onto one of the two exterior cameras per episode based on calibration quality. The episode metadata field `source.camera_for_trace` (`exterior_image_1_left` or `exterior_image_2_left`) tells you which camera the trace corresponds to. Overlay accordingly when visualising.

## 📦 Contents

| Field | Value |
|---|---|
| HF repo | `spikefly/SemanticVLA-TraceX-240K-DROID` |
| Format | LeRobot v3.0 |
| Episodes | 56,362 |
| Frames | 16,142,421 |
| FPS | 15 |
| Robot type | `franka` |
| Source dataset | Open-X-Embodiment DROID v1.0.1 (56K dense TraceX selection) |
| Data file target | 100 MB |
| Video file target | 500 MB |

### Video streams

- `observation.images.exterior_image_1_left`
- `observation.images.exterior_image_2_left`
- `observation.images.wrist_image_left`

## 🧭 Coverage

56,362 episodes with valid dense trace from the local 56K projection selection. All three DROID camera streams (two exterior + wrist) and raw action/observation fields are preserved.

## 📂 Sibling datasets in TraceX-240K

<table>
  <tr><th>Dataset</th><th>HF Repository</th><th>Embodiment</th></tr>
  <tr><td><b>Bridge</b></td><td><a href="https://huggingface.co/datasets/spikefly/SemanticVLA-TraceX-240K-Bridge">spikefly/SemanticVLA-TraceX-240K-Bridge</a></td><td>BridgeData V2 / WidowX</td></tr>
  <tr><td><b>Fractal</b></td><td><a href="https://huggingface.co/datasets/spikefly/SemanticVLA-TraceX-240K-Fractal">spikefly/SemanticVLA-TraceX-240K-Fractal</a></td><td>Fractal / Google Robot (RT-1)</td></tr>
  <tr><td><b>BC-Z</b></td><td><a href="https://huggingface.co/datasets/spikefly/SemanticVLA-TraceX-240K-BC-Z">spikefly/SemanticVLA-TraceX-240K-BC-Z</a></td><td>BC-Z / Google Robot</td></tr>
</table>

## ✏️ Citation

If you use this dataset, please cite SemanticVLA:

```bibtex
@inproceedings{ni2026semanticvla,
  title     = {SemanticVLA: Towards Semantic Reasoning over Action Memorization via Synergistic Explicit Trace and Latent Action Planning},
  author    = {Ni, Fei and Chen, Zhuo and Yuan, Yifu and Dong, Zibin and Yao, Xianze and Luo, Shan and Hao, Jianye and Deng, Jiankang and Zafeiriou, Stefanos},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026}
}
```

## 📜 License & terms

The trace annotation labels (`trace.x` / `trace.y`) are released under the [MIT License](https://github.com/Fei-Ni/SemanticVLA_Offcial/blob/main/LICENSE) as part of the SemanticVLA code release. Use of the underlying robot trajectory data is subject to the **original source dataset terms** (Open-X-Embodiment DROID v1.0.1 (56K dense TraceX selection)). Please consult the upstream dataset license before use.