DyML-Vehicle

Dynamic Metric Learning Vehicle

Dataset Information
Modalities
Images
Introduced
2021
License
Homepage

Overview

DyML-Vehicle merges two vehicle re-ID datasets PKU VehicleID [1], VERI-Wild [1]. Since these two datasets have only annotations on the identity (fine) level, we manually annotate each image with “model” label (e.g., Toyota Camry, Honda Accord, Audi A4) and “body type” label (e.g., car, suv, microbus, pickup). Moreover, we label all the taxi images as a novel testing class under coarse level.

[1] Hongye Liu, Yonghong Tian, Yaowei Wang, Lu Pang, and Tiejun Huang. Deep relative distance learning: Tell the difference between similar vehicles. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2167–2175, 2016. 4

[2] Y. Lou, Y. Bai, J. Liu, S. Wang, and L. Duan. Veri-wild: A large dataset and a new method for vehicle re-identification in the wild. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 3230–3238, 2019. 4

Variants: DyML-Vehicle

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Metric Learning HAPPIER Hierarchical Average Precision Training for … 2022-07-05
Metric Learning CSL Dynamic Metric Learning: Towards a … 2021-03-22

Research Papers

Recent papers with results on this dataset: