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