Knowledge Commons of Institute of Automation,CAS
You Only Look One-level Feature | |
Chen, Qiang1,2; Wang, Yingming; Yang, Tong; Zhang, Xiangyu; Cheng, Jian1,2; Sun, Jian | |
2021 | |
会议名称 | IEEE Conference on Computer Vision and Pattern Recognition |
会议日期 | 2021-06-24 |
会议地点 | Online |
摘要 | This paper revisits feature pyramids networks (FPN) for one-stage detectors and points out that the success of FPN is due to its divide-and-conquer solution to the optimization problem in object detection rather than multi-scale feature fusion. From the perspective of optimization, we introduce an alternative way to address the problem instead of adopting the complex feature pyramids - utilizing only one-level feature for detection. Based on the simple and efficient solution, we present You Only Look One-level Feature (YOLOF). In our method, two key components, Dilated Encoder and Uniform Matching, are proposed and bring considerable improvements. Extensive experiments on the COCO benchmark prove the effectiveness of the proposed model. Our YOLOF achieves comparable results with its feature pyramids counterpart RetinaNet while being 2.5× faster. Without transformer layers, YOLOF can match the performance of DETR in a single-level feature manner with 7× less training epochs. Code is available at https://github.com/megvii-model/YOLOF. |
收录类别 | EI |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44919 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Chen, Qiang,Wang, Yingming,Yang, Tong,et al. You Only Look One-level Feature[C],2021. |
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 | ||
YOLOF_camera_ready.p(541KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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