Cross- Scenario Person Re-identification
文献类型：期刊论文
| 作者 | Jia,Ruoran; Liu,Shuguang
|
| 刊名 | Journal of Physics: Conference Series
 |
| 出版日期 | 2020-11-01 |
| 卷号 | 1684期号:1 |
| ISSN号 | 1742-6588 |
| DOI | 10.1088/1742-6596/1684/1/012071 |
| 英文摘要 | Abstract Person Reid is a challenging task for two factors, first one is background interference, such as changes in light, weather, posture, and camera position. Second is domain adaptive capacity, such as model train by market1501 achieve the same performance on Duke dataset. To solve the above problems, we come up with adopt human semantic to remove clutter from unwanted background information, is naturally a better alternative compare with bounding box, we adopt Local Regions Representation to extra the image features, which can preeminently improve the representation of local feature and global feature. Our proposed CSReID integrates human semantic and Local Regions Representation in person re-identification and not need to train on the evaluation dataset can achieve state of the art cross-modal performance. |
| 语种 | 英语 |
| WOS记录号 | IOP:1742-6588-1684-1-012071 |
| 出版者 | IOP Publishing |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/12416]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 作者单位 | Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Jia,Ruoran,Liu,Shuguang. Cross- Scenario Person Re-identification[J]. Journal of Physics: Conference Series,2020,1684(1). |
| APA | Jia,Ruoran,&Liu,Shuguang.(2020).Cross- Scenario Person Re-identification.Journal of Physics: Conference Series,1684(1). |
| MLA | Jia,Ruoran,et al."Cross- Scenario Person Re-identification".Journal of Physics: Conference Series 1684.1(2020). |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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