人工智能
目标检测
计算机科学
计算机视觉
管道(软件)
任务(项目管理)
分割
对象(语法)
图像分割
模式识别(心理学)
利用
对象类检测
比例(比率)
人脸检测
工程类
物理
程序设计语言
系统工程
量子力学
计算机安全
面部识别系统
作者
Gedas Bertasius,Jianbo Shi,Lorenzo Torresani
标识
DOI:10.1109/cvpr.2015.7299067
摘要
Contour detection has been a fundamental component in many image segmentation and object detection systems. Most previous work utilizes low-level features such as texture or saliency to detect contours and then use them as cues for a higher-level task such as object detection. However, we claim that recognizing objects and predicting contours are two mutually related tasks. Contrary to traditional approaches, we show that we can invert the commonly established pipeline: instead of detecting contours with low-level cues for a higher-level recognition task, we exploit object-related features as high-level cues for contour detection.
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