---
pretty_name: TriWorldBench Dataset
tags:
- benchmark
- embodied-ai
- world-model
- robotics
- evaluation
---

# TriWorldBench Dataset

Welcome to TriWorldBench, a benchmark for evaluating triple-view embodied world models.

- Benchmark homepage: [https://www.triworldbench.com](https://www.triworldbench.com)
- Benchmark code repository: [TriWorldBench/TriWorldBench](https://github.com/TriWorldBench/TriWorldBench)

## Overview

TriWorldBench evaluates world models from three synchronized robot views: head,
left wrist, and right wrist. The benchmark focuses on whether a model can generate
one coherent robot world across all three cameras while preserving task alignment,
physical and 3D coherence, motion quality, temporal consistency, and visual quality.

## Released Files

This Hugging Face dataset provides two compressed dataset bundles:

- `test_dataset`: the official 500-episode test set for leaderboard submission.
- `val_dataset`: a 100-episode validation bundle for local development and quick evaluation.

## `test_dataset` Structure

After extraction, the official test dataset is organized as:

```text
test_dataset/
+-- data/
|   +-- episode1.hdf5
|   +-- episode2.hdf5
|   +-- ...
|   +-- episode500.hdf5
+-- first_frame/
|   +-- episode1_head.jpg
|   +-- episode1_left.jpg
|   +-- episode1_right.jpg
|   +-- ...
|   +-- episode500_right.jpg
+-- instructions/
    +-- episode1.json
    +-- episode2.json
    +-- ...
    +-- episode500.json
```

The test set contains 500 episodes indexed from `episode1` to `episode500`.
For each episode, `data/episodeN.hdf5` contains the trajectory/action sequence,
`first_frame/` provides the initial 320x240 observations for the head, left wrist,
and right wrist cameras, and `instructions/episodeN.json` contains the task instruction.

Participants should run their models on this test set and submit generated videos
for all three views: `head.mp4`, `left.mp4`, and `right.mp4`.

## `val_dataset` Structure

The validation bundle contains 100 episodes derived from RoboTwin2.0, together
with the corresponding ground-truth data and processed state annotations.
After extraction, it is organized as:

```text
val_dataset/
+-- test_dataset/
|   +-- data/
|   +-- first_frame/
|   +-- instructions/
+-- STATE/
|   +-- episode*.json
+-- gt_dataset/
    +-- episode*/
```

The `val_dataset/test_dataset` folder provides the same type of model inputs as
the official test set. The bundled `gt_dataset` and `STATE` folders are already
formatted for the TriWorldBench evaluation code. Matching VQA question annotations
for this validation set are included in the benchmark code repository under
`metrics/VQA/qa_val/`.

## Evaluation and Submission

Please refer to the benchmark homepage and code repository for environment setup,
inference, evaluation, and leaderboard submission instructions.