Multi-weather vehicle dataset for camouflage generation

Citation Author(s):
Jiawei
Zhou
Harbin Institute of Technology, Shenzhen
Submitted by:
Jiawei Zhou
Last updated:
Wed, 10/16/2024 - 08:59
DOI:
10.21227/n1ce-pk06
Data Format:
License:
0
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Abstract 

This dataset is utilized for adversarial camouflage generation. We collect vehicle datasets in the CARLA simulation environment under 16 weather conditions. These weather conditions are generated by combining four sun altitude angles (-90°, 10°, 45°, 90°) with four fog densities (0, 25, 50, 90). Within each weather scenario,  we randomly choose 16 locations for texture generation. Camera transformation values are randomly selected within specified intervals at each car location. These intervals include four altitude angle intervals ([0, 22.5], [22.5, 45], [45, 67.5], [67.5, 90]), eight azimuth angle intervals([0, 45], [45, 90], ..., [315, 360]), and four distances intervals ([2.5, 7.5], [7.5, 12.5], [12.5, 17.5], [17.5, 22.5]). In total, we employ 32,768 photo-realistic images for texture generation.

 

Instructions: 

The multi-weather dateset for Audi Etron texture generation,including five folders. 
       masks: *png, the binary mask of vehicle;
       masks_segementation: *.png, the original mask of vehicle from the semantic segmentation camera  in Carla;
       train: *.npz,  including vehicle images, the camera transformation parameters, and vehicle location parameters;
       train_label_new: *.txt, the detection groundtruth;
       train_new: *.png, the vehicle image.
There are 36,758 files in each folders.