claravid / README.md
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---
license: cc-by-nc-sa-4.0
pretty_name: ClaraVid
size_categories:
- 10K<n<100K
extra_gated_heading: Access Request for ClaraVid Dataset
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You will not employ the dataset in any context that could directly or
indirectly cause harm to individuals or communities
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task_categories:
- image-to-3d
- depth-estimation
- image-segmentation
tags:
- UAV
- Aerial
- Semantic Mapping
- 3D Reconstruction
- Neural Recontruction
- NERF
- Gaussian Splatting
- Urban
- Highway
- Nature
- Rural
---
# ClaraVid Dataset
[![Project Page](https://img.shields.io/badge/Project%20Page-ClaraVid-blue?style=flat&logo=github)](https://rdbch.github.io/claravid/)
[![Dataset SDK](https://img.shields.io/badge/Dataset%20SDK-ClaraVid-green?style=flat&logo=github)](https://github.com/rdbch/claravid_code)
[![arXiv Preprint](https://img.shields.io/badge/arXiv-2503.17856-b31b1b?style=flat&logo=arXiv&logoColor=white)](https://arxiv.org/abs/2503.17856)
Official repo for: *ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling* - Accepted ICCV 2025
> If you find this useful, please consider giving us a like ❤
![ClaraVid Overview](https://rdbch.github.io/claravid/images/overview.jpg)
**ClaraVid** is a synthetic dataset built for semantic and geometric neural reconstruction from low altitude UAV/aerial imagery.
It contains **16,917 multimodal frames** collected across **8 UAV missions** over diverse environments: urban, urban high, rural, highway, and nature.
Each mission features **3 viewpoints** and altitude levels, simulating multi-UAV operations.
The dataset spans *1.8km^2*, with an average mission coverage of *0.22km^2*.
It includes visual measurements at **4032x3024** resolution for *RGB images, metric depth maps,
panoptic(semantic and instance) segmentation and dynamic object masks*. Additionally in contains *scene level pointcloud* and *camera calibration(intrinsic and extrinsic)*.
## Channel Log / TODOs
- [x] All data uploaded
- [x] Release dataset SDK
- [x] Release pip package
- [ ] Release dataset splits
- [ ] Add Nerfstudio support
- [ ] Dataset download script
- [ ] Release DSP code (closer to conference)
## 3. Download
Clone this repository and extract the data archive in the same folders. The archives were compressed using 7-Zip. We will provide a download script in the near future.
## 4. Usage
We provide a dataset SDK on [GitHub](https://github.com/rdbch/claravid_code). You can simply install it using:
```
pip install claravid
```
## 5. Dataset structure
All collection missions follow a grid pattern with both vertical and horizontal passes at a constant altitude, with a few seconds between consecutive frames.
```
claravid/
├── 001_rural_1/ # mission 1
│ ├── left_rgb/
│ │ ├── 45deg_low_h/ # 3 different viewpoints (pitch&altitude) & flying orientation in grid (horizontal or vertical passes)
│ │ │ ├── 000000.jpg
│ │ │ └── ...
│ │ ├── 45deg_low_v/
│ │ │ └── ...
│ │ ├── 55deg_mid_h/
│ │ │ └── ...
│ │ ├── 55deg_mid_v/
│ │ │ └── ...
│ │ ├── 90deg_high_h/
│ │ │ └── ...
│ │ └── 90deg_high_v/
│ │ └── ...
│ ├── depth/ # metric depth
│ │ └── ...
│ ├── panoptic_seg/ # instance (buildings, humans and vehicles) & semantic segmentation
│ │ └── ...
│ ├── semantics_colormap/ # semantic segmentation - RGB color version
│ │ └── ...
│ ├── dynamic_mask/
│ │ └── ...
│ ├── extrinsics/
│ │ └── ...
│ └── scene_pcl/ # scene level PCL (color, semantic, instance) @ various resolutions (30cm, 50cm, ...)
│ ├── panoptic_seg/
│ │ ├── global_fused_30cm.ply
│ └── ...
├── 002_rural_2/ # mission 2...
│ └── ...
└── ...
```
## 6. Mission Overview
![ClaraVid Mission Overview](https://rdbch.github.io/claravid/images/more_claravid_overview.jpg)
## 6. Data format
| **Modality** | **Directory** | **Extension** | **Description** |
|-----------------------|---------------|---------------|-----------------|
| RGB | left_rgb | .jpg | 4032 x 3024 |
| Depth | depth | .png | metric depth - \[0-1000\]m |
| Panoptic Segmentation | panoptic_seg | .png | instance (buildings, humans and vehicles) + semantic mask |
| Dynamic mask | dynamic_mask | .png | binary mask for objects that move (dynamic_elements == 0) |
| Camera Extrinsics | extrinsics | .json | in scene space (metric) |
| ScenePointcloud | scene_pcl | .ply | scene pointclouds in scene space |
Please refer to our [SDK](https://github.com/rdbch/claravid_code/blob/main/claravid/dataset.py) for more details regarding the data format.
## 7. BibTex
If you find our work useful, please consider citing:
```
@article{beche2025claravid,
title={ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling},
author={Beche, Radu and Nedevschi, Sergiu},
journal={arXiv preprint arXiv:2503.17856},
year={2025}
}
```