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This repository hosts the source code of our paper: [[CVPR 2022] Cascade Transformers for End-to-End Person Search](https://arxiv.org/abs/2203.09642). In this work, we developed a novel Cascaded Occlusion-Aware Transformer (COAT) model for end-to-end person search. The COAT model outperforms **state-of-the-art** methods on the PRW benchmark dataset by a large margin and achieves state-of-the-art performance on the CUHK-SYSU dataset.
# **COAT代码使用说明**
| Dataset | mAP | Top-1 | Model |
| --------- | ---- | ----- | ------------------------------------------------------------ |
这个存储库托管了论文的源代码:[[CVPR 2022] Cascade Transformers for End-to-End Person Search](https://arxiv.org/abs/2203.09642)。在这项工作中我们开发了一种新颖的级联遮挡感知TransformerCOAT模型用于端到端的人物搜索。COAT模型在PRW基准数据集上以显著的优势胜过了最先进的方法并在CUHK-SYSU数据集上取得了最先进的性能。
| 数据集(Datasets) | mAP | Top-1 | Model |
| ---------------- | ---- | ----- | ------------------------------------------------------------ |
| CUHK-SYSU | 94.2 | 94.7 | [model](https://drive.google.com/file/d/1LkEwXYaJg93yk4Kfhyk3m6j8v3i9s1B7/view?usp=sharing) |
| PRW | 53.3 | 87.4 | [model](https://drive.google.com/file/d/1vEd_zzFN88RgxbRMG5-WfJZgD3vmP0Xg/view?usp=sharing) |