Eliminating Background-bias for Robust Person Re-identification学习笔记
我是一个期待骚操作的人，可能写博客正好满足了我的这种需求，所以我竟然坚持了很久，让自己都会有点意外。 今天学习的这篇论文叫“为了更加鲁棒的ReID系统消除背景偏置带来的影响”。 直观的先给大家看看背景带来的影响：第一张图是原图，第二张图排序是对的，他和第一张图是相似的，但是第三张图和第四张图的排序却出现了错误，这里将同一背景下的不同人与不同背景下的同一人发生了排序混淆，说明背景的存在对于ReID是
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相关文章
- 1. 2018-CVPR-Eliminating Background-bias for Robust Person Re-identification（消除背景偏差）
- 2. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 论文笔记
- 3. 【Robust学习笔记】Inventory Management Based on Target-Oriented Robust Optimization
- 4. 学习笔记：Saliency Optimization from Robust Background Detection
- 5. Adversarially Occluded Samples for Person Re-identification学习笔记
- 6. Group Consistent Similarity Learning via Deep CRF for Person Re-Identification学习笔记
- 7. End-to-End Deep Kronecker-Product Matching for Person Re-identification学习笔记
- 8. Harmonious Attention Network for Person Re-Identification学习笔记
- 9. Camera Style Adaptation for Person Re-identification-学习笔记
- 10. Mask-guided Contrastive Attention Model for Person Re-Identification学习笔记