allenai/WildDet3D-Stereo4D-Bench

---
license: cc-by-nc-4.0
task_categories:
- object-detection
tags:
- 3d-object-detection
- 3d-bounding-box
- stereo
- benchmark
pretty_name: WildDet3D Stereo4D Benchmark
size_categories:
- 1K<n<10K
---

# WildDet3D Stereo4D Benchmark

3D object detection benchmark with ground-truth stereo depth from Stereo4D.

Images extracted from Stereo4D videos (1 frame per video from the test set, representing 7% of all Stereo4D videos).

| Split | Images | Annotations |
|-------|--------|-------------|
| Val | 383 | 2,782 |

**Note:** The test set is held out for hidden evaluation and is not publicly available.

## Download

```bash
pip install huggingface_hub

# Download everything
huggingface-cli download weikaih/WildDet3D-Stereo4D-Bench --repo-type dataset --local-dir WildDet3D-Stereo4D-Bench
```

After downloading, extract the packed archives:

```bash
cd WildDet3D-Stereo4D-Bench
tar xzf packed/images.tar.gz
tar xzf packed/depth.tar.gz
tar xzf packed/camera_parameters.tar.gz
```

## Directory Structure

```
WildDet3D-Stereo4D-Bench/
├── annotations/
│ ├── Stereo4D_val.json
│ ├── Stereo4D_test.json
│ └── Stereo4D_val_class_map.json
├── images/ # 7,704 images (512x512)
├── depth/ # 7,704 .npy depth maps (float32, meters)
└── camera_parameters/ # 7,704 .json camera intrinsics
```

## Annotation Format (COCO3D)

Same format as [WildDet3D-Data](https://huggingface.co/datasets/weikaih/WildDet3D-Data). Each annotation JSON contains:

- **`images`**: image metadata with `file_path`, `K` (intrinsics), `width`, `height`
- **`annotations`**: 3D bounding boxes with `center_cam`, `dimensions` [W,H,L], `R_cam`, `bbox3D_cam`, `bbox2D_proj`, `valid3D`
- **`categories`**: category list

## Depth Format

Each `.npy` file is a float32 2D array at image resolution (512x512). **Values are in meters.**

## License

CC BY-NC

This dataset is licensed under CC BY-NC. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.