| --- |
| license: mit |
| task_categories: |
| - image-classification |
| - object-detection |
| tags: |
| - carla |
| - uav |
| - visual-search |
| - robotics |
| - embodied-ai |
| pretty_name: CW-AVIS |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # CW-AVIS |
|
|
| CW-AVIS is a CARLA-based benchmark dataset for cross-weather aerial visual |
| instance search. It pairs target descriptions and search start poses with |
| reference images captured under multiple weather and lighting conditions. |
|
|
| The dataset accompanies [ReF-AVS](https://github.com/GoryZoi/ReF-AVS). |
|
|
| ## Contents |
|
|
| - 2,470 PNG reference images |
| - 61 target definitions across six CARLA towns |
| - Three search difficulties: easy, medium, and hard |
| - Clear, cloudy, rainy, wet, night, sunset, and dust-storm conditions |
| - Total uncompressed size: approximately 2.99 GB (2.78 GiB) |
|
|
| ```text |
| CW-AVIS/ |
| targets_Town01/ |
| 101_Bus_Stop_in_Front_of_Terrace_Restaurant_by_Bridge/ |
| target.json |
| ref_Clear Noon/ |
| *.png |
| ref_Wet Night/ |
| *.png |
| targets_Town02/ |
| targets_Town03/ |
| targets_Town04/ |
| targets_Town05/ |
| targets_Town10HD/ |
| ``` |
|
|
| Each `target.json` includes a numeric target ID, target name, natural-language |
| scene hint, ground-truth final XY position, initial UAV poses for each |
| difficulty, and the number of reference images available per weather. |
|
|
| ## Usage |
|
|
| Download the repository and point ReF-AVS to its root: |
|
|
| ```bash |
| export REF_AVS_DATASET_DIR=/path/to/CW-AVIS |
| python main/run_rivas_batch.py --dataset "$REF_AVS_DATASET_DIR" |
| ``` |
|
|
| `SHA256SUMS` contains checksums for every PNG and JSON payload file. |
|
|
| ## License |
|
|
| The dataset metadata and annotations are released under the MIT License. CARLA |
| simulation assets remain subject to their applicable upstream terms. |
|
|
