Datasets:

TencentARC
/

GameHorizon-Data

---
license: apache-2.0
task_categories:
  - video-text-to-text
language:
  - en
tags:
  - gameplay
  - video
  - instruction-following
  - long-horizon
  - agents
pretty_name: GameHorizon-Data
size_categories:
  - n<1K
---

# GameHorizon-Data

The data home of **[GameHorizon Suite](https://gamehorizon-suite.github.io)** — a
unified data and evaluation suite for gameplay capabilities across temporal horizons.
This repository hosts the AAA gameplay recordings, the temporally aligned
keyboard-mouse action streams, the multi-horizon instruction annotations, and the
benchmark question sets.

- 📄 Paper: [arXiv:2609.25001](https://arxiv.org/abs/2609.25001)
- 💻 Code: [TencentARC/GameHorizon](https://github.com/TencentARC/GameHorizon)
- 🌐 Project page: https://gamehorizon-suite.github.io

## 🚀 Release plan

Everything is released here progressively. **The annotator demo and the keybind maps
are live now**; the rest is being prepared.

- [x] 🎬 **`GameHorizon-Annotator-Demo/`** — six annotated scenes to run the pipeline on
- [x] ⌨️ **`keybinds/`** — key-to-action maps for all 21 titles
- [ ] 📊 **GameHorizon-Bench (offline)** — the standardized question sets behind the
      three primary tasks and the diagnostic variants
- [ ] 📊 **GameHorizon-Bench (online)** — task specifications and environment states
      for the stepwise online track
- [ ] 🎯 **GameHorizon-Data (full)** — 5,000 hours of human gameplay across 21 titles:
      4,571 videos at 60 fps, 411.03 M keyboard-mouse events, and 6,184,036
      instructions (5,947,588 short-horizon, 189,158 medium-horizon, 47,290
      long-horizon)

Watch this repository, or the
[GitHub repo](https://github.com/TencentARC/GameHorizon), to follow progress.

## 🎬 `GameHorizon-Annotator-Demo/`

Six annotated gameplay scenes, one folder each. Every folder holds the recording,
the per-frame keyboard-mouse stream, and the three levels of instructions.

| Scene | Game | Frames | Span | Level 1 / 2 / 3 |
| --- | --- | --- | --- | --- |
| `ApexLegends` | Apex Legends | 9,972 | 603 s | 191 / 7 / 3 |
| `Cyberpunk2077` | Cyberpunk 2077 | 5,253 | 337 s | 94 / 4 / 1 |
| `EldenRing` | Elden Ring | 9,884 | 632 s | 419 / 8 / 2 |
| `EldenRing_NightReign` | Elden Ring Nightreign | 4,843 | 311 s | 143 / 4 / 2 |
| `GTA5` | GTA V | 4,901 | 313 s | 74 / 4 / 1 |
| `Minecraft` | Minecraft | 5,237 | 331 s | 92 / 4 / 1 |

```
GameHorizon-Annotator-Demo/<Scene>/
├── <recording>.mkv                          # full session, 60 fps
├── <scene>_annotations_per_frame.json       # per-frame keyboard and mouse events
├── level_1_instructions.json                # short-horizon operations
├── level_2_instructions.json                # medium-horizon goals
└── level_3_instructions.json                # long-horizon strategies
```

**`*_annotations_per_frame.json`** — one entry per sampled frame under `frames`,
with the scene's bounds and event counts at the top level.

```json
{
  "scene_name": "...", "interval_start_ns": 0, "interval_end_ns": 0,
  "num_frames": 5237, "stats": {},
  "frames": [{
    "frame_index": 42,
    "timestamp_ns": 1784308897688733400,
    "next_frame_timestamp_ns": 1784308897751233400,
    "width": 1920, "height": 1080,
    "keyboard_events":  [{"timestamp_ns": 0, "event_type": "press", "vk": 32, "key_name": "SPACE"}],
    "raw_mouse_events": [{"timestamp_ns": 0, "dx": -6, "dy": 6,
                          "button_flags": "0", "button_data": 0, "button_flag_names": []}],
    "mouse_events":     [{"timestamp_ns": 0, "event_type": "move", "x": 1279, "y": 822}]
  }]
}
```

`raw_mouse_events` is the Windows RawInput stream: `dx`/`dy` are relative deltas
(`dx > 0` rightward, `dy > 0` downward) and `button_flag_names` holds `RI_MOUSE_*`
constants. `mouse_events` is the derived view of the same input — `move` with
absolute `x`/`y`, `click` with `button`/`pressed`, `scroll` with `dx`/`dy`.

Timestamps are absolute wall-clock nanoseconds shared with the recording, which is
how frames and actions stay aligned. The annotation covers one scene out of the full
session, located through the video's `creation_time`, so keep the recording intact.

**`level_{1,2,3}_instructions.json`** — one entry per clip under `items`, in temporal
order.

```json
{
  "schema_version": 2, "game_id": "minecraft", "level": 1,
  "model": "gemini-3.5-flash", "prompt_version": "detailed-v2-mouse",
  "items": [{
    "scene": "scene_000000",
    "order": 0,
    "level": 1,
    "duration_s": 8.41,
    "instruction": "Strafe right and jump along the crimson cliffside in the Nether ...",
    "source_scenes": [],
    "sampled_frame_refs": ["frames_level_1/scene_000000/000000.jpg"],
    "status": "ok"
  }]
}
```

`source_scenes` lists the lower-level clips a Level-2 or Level-3 instruction was
merged from, which is what links the three horizons into one pyramid.
`sampled_frame_refs` records the frames the model saw.

## ⌨️ `keybinds/`

Key-to-action maps for all 21 titles, one JSON per game: a flat mapping from raw
`KEY_*` / `RI_MOUSE_*` event names to their in-game meaning.

```json
{
  "KEY_W": "Move Forward",
  "LCONTROL": "Sprint",
  "KEY_E": "Open/Close Inventory",
  "RI_MOUSE_LEFT_BUTTON_DOWN": "Attack / Destroy Block"
}
```

`apex_legends` · `assassins_creed` · `black_myth_wukong` · `cyberpunk_2077` ·
`delta_force` · `eldenring` · `eldenring_nightreign` · `escape_from_tarkov` ·
`genshin_impact` · `gta5` · `honor_of_kings_world` · `minecraft` ·
`neverness_to_everness` · `palworld` · `pubg` · `red_dead_redemption_2` ·
`roco_kingdom_world` · `the_witcher_3` · `valorant` · `watch_dogs_2` ·
`wuthering_waves`

## 📥 Download

```bash
hf download TencentARC/GameHorizon-Data --repo-type dataset --local-dir ./GameHorizon-Data

# or a subset
hf download TencentARC/GameHorizon-Data --repo-type dataset \
  --include 'keybinds/*' --local-dir ./GameHorizon-Data
```

## 📜 License

Apache-2.0. The gameplay recordings are released for research use; all game
content remains the property of its respective publishers.

## 📖 Citation

```bibtex
@article{GameHorizonSuite2026,
      title={GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay},
      author={Yiran Wang and Xingyilang Yin and Junfu Pu and Guangzhi Wang and Kaifeng Li and Mingyu Ouyang and Huiqiang Sun and Lingen Li and Cheng Cheng and Wangbo Yu and Honghao Chen and Xiaodong Cun and Chi-Man Pun and Zhiguo Cao and Ying Shan},
      year={2026},
      journal={arXiv preprint arXiv:2609.25001},
      url={https://arxiv.org/abs/2609.25001},
}
```