Deep Learning for Person Re-identification: A Survey and Outlook——準研究生論文週報
1 簡介 這是一篇綜述性文章，本文從closed-world和open-world兩個方面較細緻地分析了Re-ID，並展望了前景。這次的心得寫得較長，也算是一個總結。 首先，作者通過將Re-ID分爲封閉世界(closed-world)的ReID和開放世界(open-world)的Re-ID來陳述，如下表，通俗地說，closed-world指的就是較爲理想的環境下的實驗，比如單模態的數據集、
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相關文章
- 1. 2020Arxiv之ReID：Deep Learning for Person Re-identification: A Survey and Outlook論文筆記
- 2. Person Re-Identification by Deep Joint Learning of Multi-Loss Classification——準研究生論文週報
- 3. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 4. Unsupervised Person Re-identification via Multi-label Classification——準研究生論文週報
- 5. 【論文筆記】Deep Learning on Graphs: A Survey
- 6. Deep Learning based Recommender System: A Survey and New Perspectives
- 7. 基於深度學習的person re-identification綜述 Deep Learning for Person Re-identification: A Survey and Outlook
- 8. Deep Learning on Graphs: A Survey論文筆記
- 9. (ch8) Deep Learning for Anomaly Detection: A Survey
- 10. AdderNet: Do we really need multiplications in deep learning——準研究生論文週報