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【Person Re-id】A Discriminatively Learned CNN Embedding for Person Re-identification
时间 2021-01-07
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loss
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verification model:同时输入image pairs,network预测输入图片是否为同一个人,将问题当成一个二分类来看。这样导致没有完全用到标注信息,image pairs和数据集中的其他图片的关系被忽略了。 identification model:将Person Re-id问题看做一个multi-class recognition task,利用数据的原始标注信息结合cros
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相关文章
1.
1611.A Discriminatively Learned CNN Embedding for Person Re-identification论文阅读笔记
2.
A Discriminatively Learned CNN Embedding for Person Re-identification 论文记录
3.
ReID论文笔记1-Deeply-Learned Part-Aligned Representations for Person Re-Identification
4.
Norm-Aware Embedding for Efficient Person Search
5.
论文笔记:Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
6.
SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification (note)
7.
part-aligned系列论文:1707.Deeply-Learned Part-Aligned Representations for Person Re-Identification 论文笔记
8.
【ReID】【skimming】SphereReID: Deep Hypersphere Manifold Embedding for Person Re-identification
9.
【ReID】Batch DropBlock Network for Person Re-identification and Beyond
10.
【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
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