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21 classes
0ref_Clear Night
0ref_Clear Night
0ref_Clear Night
1ref_Clear Noon
1ref_Clear Noon
1ref_Clear Noon
2ref_Clear Sunset
2ref_Clear Sunset
2ref_Clear Sunset
3ref_Cloudy Night
3ref_Cloudy Night
3ref_Cloudy Night
4ref_Cloudy Noon
4ref_Cloudy Noon
4ref_Cloudy Noon
5ref_Cloudy Sunset
5ref_Cloudy Sunset
5ref_Cloudy Sunset
6ref_Dust Storm
6ref_Dust Storm
6ref_Dust Storm
7ref_Hard Rain Noon
7ref_Hard Rain Noon
7ref_Hard Rain Noon
8ref_Hard Rain Sunset
8ref_Hard Rain Sunset
8ref_Hard Rain Sunset
9ref_Mid Rain Sunset
9ref_Mid Rain Sunset
9ref_Mid Rain Sunset
11ref_Mid Rainy Noon
11ref_Mid Rainy Noon
11ref_Mid Rainy Noon
12ref_Soft Rain Night
12ref_Soft Rain Night
12ref_Soft Rain Night
13ref_Soft Rain Noon
13ref_Soft Rain Noon
13ref_Soft Rain Noon
14ref_Soft Rain Sunset
14ref_Soft Rain Sunset
14ref_Soft Rain Sunset
15ref_Wet Cloudy Night
15ref_Wet Cloudy Night
15ref_Wet Cloudy Night
16ref_Wet Cloudy Noon
16ref_Wet Cloudy Noon
16ref_Wet Cloudy Noon
17ref_Wet Cloudy Sunset
17ref_Wet Cloudy Sunset
17ref_Wet Cloudy Sunset
18ref_Wet Night
18ref_Wet Night
18ref_Wet Night
19ref_Wet Noon
19ref_Wet Noon
19ref_Wet Noon
20ref_Wet Sunset
20ref_Wet Sunset
20ref_Wet Sunset
0ref_Clear Night
0ref_Clear Night
1ref_Clear Noon
1ref_Clear Noon
2ref_Clear Sunset
2ref_Clear Sunset
3ref_Cloudy Night
3ref_Cloudy Night
4ref_Cloudy Noon
4ref_Cloudy Noon
5ref_Cloudy Sunset
5ref_Cloudy Sunset
6ref_Dust Storm
6ref_Dust Storm
7ref_Hard Rain Noon
7ref_Hard Rain Noon
8ref_Hard Rain Sunset
8ref_Hard Rain Sunset
9ref_Mid Rain Sunset
9ref_Mid Rain Sunset
11ref_Mid Rainy Noon
11ref_Mid Rainy Noon
12ref_Soft Rain Night
12ref_Soft Rain Night
13ref_Soft Rain Noon
13ref_Soft Rain Noon
14ref_Soft Rain Sunset
14ref_Soft Rain Sunset
15ref_Wet Cloudy Night
15ref_Wet Cloudy Night
16ref_Wet Cloudy Noon
16ref_Wet Cloudy Noon
17ref_Wet Cloudy Sunset
17ref_Wet Cloudy Sunset
18ref_Wet Night
18ref_Wet Night
19ref_Wet Noon
19ref_Wet Noon
20ref_Wet Sunset
20ref_Wet Sunset
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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.

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)
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:

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.

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