論文筆記之--Joint Detection and Identification Feature Learning for Person Search
轉自：http://blog.csdn.net/he_is_all/article/details/60331997 Abstract： 現有的行人再識別方法中所使用的標準和方法主要關注的是經過裁剪的行人照片，這與現實生活場景中的圖片有所不同。本文爲了縮小兩者的差距，提出了一種行人搜索的新框架，將行人檢測和行人再識別結合起來，利用單個CNN來進行訓練。文中使用了 OIM損失（Online Inst
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相關文章
- 1. 1604.Joint Detection and Identification Feature Learning for Person Search論文閱讀筆記
- 2. Person search: Joint Detection and Identification Feature Learning for Person Search筆記
- 3. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
- 4. Joint Discriminative and Generative Learning for Person Re-identification
- 5. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
- 6. 2020Arxiv之ReID：Deep Learning for Person Re-identification: A Survey and Outlook論文筆記
- 7. 【論文筆記】Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
- 8. [CVPR2019]Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification論文筆記
- 9. 論文閱讀筆記之RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
- 10. 1604.An Enhanced Deep Feature Representation for Person Re-identification 論文筆記