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【ReID】Hierarchical and Efficient Learning for Person Re-Identification
時間 2021-01-02
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ReID
深度學習
機器學習
人工智能
計算機視覺
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剛出的arvix,Hierarchical and Efficient Learning for Person Re-Identification。文章提出了結合global 和local feature和由多種loss聯合監督的恢復feature的多層級高效網絡。還改進了Random Erasing方法,將方形擦除區域改爲了多邊形(Random Polygon Erasing (RPE)),還提
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相關文章
1.
【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification
2.
【ReID】Batch DropBlock Network for Person Re-identification and Beyond
3.
Joint Discriminative and Generative Learning for Person Re-identification
4.
1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
5.
Person search: Joint Detection and Identification Feature Learning for Person Search筆記
6.
【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
7.
1607.CVPR-Joint Learning of Single-image and Cross-image Representations for Person ReID 論文筆記
8.
2020Arxiv之ReID:Deep Learning for Person Re-identification: A Survey and Outlook論文筆記
9.
CS231n Lecture 15 | Efficient Methods and Hardware for Deep Learning
10.
Norm-Aware Embedding for Efficient Person Search
>>更多相關文章<<