# MetricScenes

A metrically-grounded, in-the-wild dataset. For more details, please visit the [project page](https://metricscenes.github.io/).

## Paper

**Title:** Honey, I Shrunk the Arc de Triomphe!   
**Authors:** Yuanbo Xiangli, Hanyu Chen, Xueqing Tsang, Noah Snavely  
**Project page:** https://metricscenes.github.io/  

### Abstract

Metric scale monocular geometry estimation has seen significant progress through large-scale data aggregation, yet current foundation models suffer from a persistent ''scale-collapse'' phenomenon: distant landmarks and vast landscapes are metrically underestimated. This performance gap stems from a training data bottleneck, where existing metric-scale datasets are hardware-constrained to unvaried street-level LiDAR or short-range indoor scans, or consist of synthetic data that lacks the semantic complexity of the physical world. To bridge this gap, we curate a new metrically-grounded, in-the-wild dataset that we call Metricscenes, gathered from a variety of sources including Internet photo collections and stereo imagery. We estimate camera poses and initial depth maps for each scene using off-the-shelf methods, and recover absolute scale from geo-tagged metadata as well as known stereo camera baselines. We also improve the quality of depth maps derived from MetricScenes via a new two-stage Poisson completion method. Fine-tuning MoGe-2 on our dataset significantly mitigates scale-collapse and achieves superior metric accuracy in unconstrained, open-domain scenes while maintaining state-of-the-art performance on standard benchmarks.
## Release Structure

MetricScenes is aggregated from AerialMegaDepth, MegaScenes, and Stereo4D. We develop pipelines to extract metric-scale depth maps in each case.
The public release is organized as dataset_name/scene_id/frame_id/...:

```text
MetricScenes/
├── AerialMegaDepth/
│   ├── 0000
│   │   ├── 1000570923_c2a177031b_o
│   │   │   ├── depth_complete.png
│   │   │   ├── depth_partial.png
│   │   │   ├── image.jpg
│   │   │   └── meta.json
│   │   ├── 1001414672_f286cdb145_o
│   │   │   └── ...
│   │   └── ...
│   ├── 0001
│   │   └── ...
│   └── ...
├── MegaScenes/
│   ├── 000
│   │   ├── 000352
│   │   │   ├── depth_complete.png
│   │   │   ├── depth_partial.png
│   │   │   ├── image.jpg
│   │   │   └── meta.json
│   │   ├── 000373
│   │   │   └── ...
│   │   └── ...
│   ├── 001
│   │   └── ...
│   └── ...
├── Stereo4D/
│   ├── -3Sx43OYGJ8
│   │   ├── 15081748_f99
│   │   │   ├── depth_complete.png
│   │   │   ├── depth_partial.png
│   │   │   ├── image.jpg
│   │   │   └── meta.json
│   │   ├── 21755088_f99
│   │   │   └── ...
│   │   └── ...
│   ├── -5JaYFNtYlM
│   │   └── ...
│   └── ...
│  
└── README.md
```

depth_partial.png is the incomplete depth from SfM/MVS or off-the-shelf geometric models; 
depth_complete.png is the completed depth using our proposed two-stage edge-aware Poisson completion method;
image.jpg is the RGB image;
meta.json contains camera parameters like intrinsics, extrinsics etc. 

## Licensing Metadata

The MetricScenes dataset is licensed under the Creative Commons Attribution 4.0 International License. **The original images come with their own licenses.**