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VSW

Vehicle search in the Wild: A New Benchmark

VSW_v1

Description

Note that, we publish only part of the data, also for the initial version. It contains 76,387 frames and 475 ids. We split the dataset into a train and a test subset, ensuring no overlapped images or labeled identities between them. The train set contains 38,280 frames and 254 training IDs, the first 99 are cross-camera ids. The test set contains 38,280 frames and 254 training IDs, the first 97 are cross-camera ids. Then for each vehicle in the test set, we randomly select two bounding boxes as query vehicles under each camera.

  • This dataset is organized as follows:

├── annotations               # Annotation of frames
│   ├── */*.mat                       
├── frames                    # the vehicle frames
│   ├── */*.jpg                        
├── query                     # query set
│   ├── */*.jpg               
├── frame_train.mat           # frames for model training
├── frame_test.mat            # frames for model testing
├── ID_train.mat              # IDs for model training
├── ID_test.mat               # IDs for model testing
├── query_info.txt            # query set

Citation

If you find our dataset useful in your research work, please consider citing:

bib:

@inbook{10.1145/3474085.3475654,
title = {Unsupervised Vehicle Search in the Wild: A New Benchmark},
author = {Zhong, Xian and Zhao, Shilei and Wang, Xiao and Jiang, Kui and Liu, Wenxuan and Huang, Wenxin and Wang, Zheng},
booktitle = {Proceedings of the 29th ACM International Conference on Multimedia},
year = {2021},
pages = {5316–5325},
}

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