Knowledge Commons of Institute of Automation,CAS
Identity-Guided Human Semantic Parsing for Person Re-Identification | |
Zhu Kuan; Guo Haiyun; Liu Zhiwei; Tang Ming; Wang Jinqiao | |
2020-07 | |
会议名称 | European Conference on Computer Vision 2020 |
会议日期 | 2020-7 |
会议地点 | 线上 |
摘要 | Existing alignment-based methods have to employ the pre-trained human parsing models to achieve the pixel-level alignment, and cannot identify the personal belongings (e.g., backpacks and reticule) which are crucial to person re-ID. In this paper, we propose the identity-guided human semantic parsing approach (ISP) to locate both the human body parts and personal belongings at pixel-level for aligned person re-ID only with person identity labels. We design the cascaded clustering on feature maps to generate the pseudo-labels of human parts. Specifically, for the pixels of all images of a person, we first group them to foreground or background and then group the foreground pixels to human parts. The cluster assignments are subsequently used as pseudo-labels of human parts to supervise the part estimation and ISP iteratively learns the feature maps and groups them. Finally, local features of both human body parts and personal belongings are obtained according to the self-learned part estimation, and only features of visible parts are utilized for the retrieval. Extensive experiments on three widely used datasets validate the superiority of ISP over lots of state-of-the-art methods. Our code is available at https://github.com/CASIA-IVA-Lab/ISP-reID. |
收录类别 | EI |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
国重实验室规划方向分类 | 语音语言处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51929 |
专题 | 紫东太初大模型研究中心 |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
推荐引用方式 GB/T 7714 | Zhu Kuan,Guo Haiyun,Liu Zhiwei,et al. Identity-Guided Human Semantic Parsing for Person Re-Identification[C],2020. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
ISP.pdf(1287KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论