图 书 馆
整体嵌套边缘检测Holistically-Nested Edge Detection |
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| 课程网址: | http://videolectures.net/iccv2015_xie_edge_detection/ |
| 主讲教师: | Saining Xie |
| 开课单位: | 加州大学圣地亚哥分校计算机科学与工程系 |
| 开课时间: | 2016-02-10 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We develop a new edge detection algorithm that addresses two important issues in this long-standing vision problem: (1) holistic image training and prediction; and (2) multi-scale and multi-level feature learning. Our proposed method, holistically-nested edge detection (HED), performs image-to-image prediction by means of a deep learning model that leverages fully convolutional neural networks and deeply-supervised nets. HED automatically learns rich hierarchical representations (guided by deep supervision on side responses) that are important in order to resolve the challenging ambiguity in edge and object boundary detection. We significantly advance the state-of-the-art on the BSD500 dataset (ODS F-score of.782) and the NYU Depth dataset (ODS F-score of.746), and do so with an improved speed (0.4s per image) that is orders of magnitude faster than some recent CNN-based edge detection algorithms. |
| 关 键 词: | 整体嵌套; 边缘检测; 视觉问题; 图像训练 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-04-24：chenxin01 |
| 最后编审: | 2023-05-18：chenxin01 |
| 阅读次数: | 60 |