iLIDS 全称 International Logistic Identification，是一个关于被遮挡行人重识别的图像数据集。该数据集包含了 119 个行人的 476 张图像，其中部分图像中的行人被其他人或行李遮挡。这些图像由 4 台非重叠相机拍摄。测试集包含 238 张图像，验证集包含 238 张图像。 该数据集可用于训练学习模型 FPR（Foreground-aware Pyramid Reconstruction），进而解决被遮挡行人重识别这一问题。

Citation

@inproceedings{he2018deep, title={Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach}, author={He, Lingxiao and Liang, Jian and Li, Haiqing and Sun, Zhenan}, booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2018} } @inproceedings{he2019foreground, title={Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification}, author={He, Lingxiao and Wang, Yinggang and Liu, Wu and Zhao, He and Sun, Zhenan and Feng, Jiashi}, booktitle={IEEE International Conference on Computer Vision (ICCV)}, year={2019} }