---
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.