C-FCN: Corners-based fully convolutional network for visual object detection
文献类型：期刊论文
| 作者 | Jiao, Lin1,2; Wang, Rujing1 ; Xie, Chengjun1
|
| 刊名 | MULTIMEDIA TOOLS AND APPLICATIONS
 |
| 出版日期 | 2020-08-06 |
| 关键词 | Object detection Anchor-free Corners Region proposals Fully convolutional network |
| ISSN号 | 1380-7501 |
| DOI | 10.1007/s11042-020-09503-3 |
| 通讯作者 | Xie, Chengjun(cjxie@iim.ac.cn) |
| 英文摘要 | Object detection has achieved significantly progresses in recent years. Proposal-based methods have become the mainstream object detectors, achieving excellent performance on accurate recognition and localization of objects. However, region proposal generation is still a bottleneck. In this paper, to address the limitations of conventional region proposal network (RPN) that defines dense anchor boxes with different scales and aspect ratios, we propose an anchor-free proposal generator named corner region proposal network (CRPN) which is based on a pair of key-points, including top-left corner and bottom-right corner of an object bounding box. First, we respectively predict the top-left corners and bottom-right corners by two sibling convolutional layers, then we obtain a set of object proposals by grouping strategy and non-maximum suppression algorithm. Finally, we further merge CRPN and fully convolutional network (FCN) into a unified network, achieving an end-to-end object detection. Our method has been evaluated on standard PASCAL VOC and MS COCO datasets using a deep residual network. Experiment results present that the proposed method outperforms previous detectors in the term of precision. Additionally, it runs with a speed of 76 ms per image on a single GPU by using ResNet-50 as the backbone, which is faster than other detectors. |
| WOS关键词 | FACE DETECTION ; GRADIENTS ; FEATURES |
| 资助项目 | National Natural Science Foundation of China[31671586] ; National Natural Science Foundation of China[61773360] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000556646300001 |
| 出版者 | SPRINGER |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/44941]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Xie, Chengjun |
| 作者单位 | 1.Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jiao, Lin,Wang, Rujing,Xie, Chengjun. C-FCN: Corners-based fully convolutional network for visual object detection[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2020. |
| APA | Jiao, Lin,Wang, Rujing,&Xie, Chengjun.(2020).C-FCN: Corners-based fully convolutional network for visual object detection.MULTIMEDIA TOOLS AND APPLICATIONS. |
| MLA | Jiao, Lin,et al."C-FCN: Corners-based fully convolutional network for visual object detection".MULTIMEDIA TOOLS AND APPLICATIONS (2020). |
入库方式： OAI收割
来源：合肥物质科学研究院
浏览0
下载0
收藏0
其他版本
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。