2018-ECCV-Beyond Part Models:Person Retrieval with Refined Part Pooling论文笔记
2018-ECCV-Beyond Part Models:Person Retrieval with Refined Part Pooling论文笔记 一、提出问题 本文主要研究基于分块特征的re-id方法，目前的基于分块特征的方法性能较好，但是一方面这些方法利用了额外的信息(pose estimation等)，另一方面因为目标域与源域的差异性，这些方法产生局部块的模型精度相对不高而且容易引入噪声
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相关文章
- 1. 【论文笔记-02】Beyond Part Model Person Retrieval with Refined Part Pooling
- 2. Beyond Part Models: Person Retrieval with Refined Part Pooling[论文笔记]
- 3. Beyond Part Models- Person Retrieval with Refined Part Pooling
- 4. Beyond Part Models: Person Retrieval with Refined Part Pooling (ECCV2018)
- 5. 论文之Beyond Part Models: Person Retrieval with Refined Part Pooling
- 6. 《Beyond Part Models: Person Retrieval with Refined Part Pooling 》PCB论文解读
- 7. 读论文Beyond Part Models Person Retrieval with Refined Part Pooling
- 8. [论文阅读] Beyond part models: Person retrieval with refined part pooling
- 9. 论文笔记 Beyond Part Models: Person Retrieval with Refined Part Pooling_ECCV_2018
- 10. part-aligned系列论文：1711.Beyond Part Models- Person Retrieval with Refined Part Pooling 论文阅读笔记