Deep Spatial Feature Reconstruction for Partial Person Re-identification: Freestyle Approach 阅读笔记

时间 2021-01-12

标签行人再识别 CVPR2018 繁體版

原文原文链接

这是CVPR 2018上的论文，论文针对局部行人再识别提出一种更高效率高准确率的方法，中文直译深度空域特征重建，Deep Spatial Feature Reconstruction。论文链接：https://arxiv.org/abs/1801.00881 局部行人再识别是一个很有现实意义的挑战。所谓局部是指，在无约束环境中，行人容易被遮挡，有姿势和视角变化，所以有时只有局部的行人图像可用

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1. Deep Spatial Feature Reconstruction for Partial Person Re-identification: Freestyle Approach（CV18）
2. Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-free Approach笔记
3. Deep Spatial Feature Reconstruction for Partial Person Re-identification Alignment-Free Approach(nt)
4. person ReID（行人重识别）2018CVPR paper阅读笔记
5. 1705.IAN- The Individual Aggregation Network for Person Search 论文阅读笔记
6. Pose-Guided Feature Alignment for Occluded Person Re-Identification阅读笔记
7. Feature Pyramid Networks for Object Detection 阅读笔记
8. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 论文笔记
9. 1604.Joint Detection and Identification Feature Learning for Person Search论文阅读笔记
10. Center Loss: A Discriminative Feature Learning Approach for Deep Face Recognition（论文阅读笔记）

>>更多相关文章<<