一篇BMVC18的论文,关于semantic keypoints matching.dense matching的工作,感觉比纯patch matching有意思,记录一下. 1. 摘要 提出一种针对correspondence matching的直接解决方案.没有采用一贯的基于正负样本对(一般需要困难负样本挖掘)的解决方案,本文提出了一种相似性热图生成器(similarity heatmap generator )来直接处理.对于所有query points直接在目标图像中生成相似性热图.结果…

BACKGROUND Computer viruses are a common problem for computer users. One typical mode of attack is to send an electronic mail message (e-mail) containing a file attachment to an unsuspecting user's computer. The file attachment contains malicious att…

设备控制台 (DevCon.exe) 示例 本部分提供以下设备控制台 (DevCon.exe) 命令的示例: DevCon HwIDs 示例 1:查找所有硬件 ID 示例 2:使用模式查找硬件 ID 示例 3:使用类查找硬件 ID DevCon Classes 示例 4:列出本地计算机上的类 示例 5:列出远程计算机上的类 DevCon ListClass 示例 6:列出设备安装程序类中的设备 示例 7:列出远程计算机上多个类中的设备 DevCon DriverFiles 示例 8:列出所有驱动…

1. Introduction In this work, inspired by metric learning based on deep neural features and memory augment neural networks, authors propose matching networks that map a small labelled support set and an unlabelled example to its label. Then they defi…

Abstract Input: A query image Source: A point cloud reconstruction of a large scene (有一百多万3D点) Result:pose 关键:an efficient and effective search method to establish matches between image features and scene points needed for pose estimation. 一个动态搜多额外匹配…

By Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg. Introduction SSD is an unified framework for object detection with a single network. You can use the code to train/evaluate a network for o…

Meta Learning/ Learning to Learn/ One Shot Learning/ Lifelong Learning 2018-08-03 19:16:56 本文转自:https://github.com/floodsung/Meta-Learning-Papers 1 Legacy Papers [1] Nicolas Schweighofer and Kenji Doya. Meta-learning in reinforcement learning. Neural…

HALCON 10.0  II-B 3.1 Gray-Value-Based Matching 基于灰度的匹配是一个非常经典的方法,它仅适用于对象的不模糊,不缺失,灰度值不变化.适用于对象旋转转.注意对 于所有的应用,相关性和基于形状的匹配是要优先考虑的.使用灰度匹配的理由可能是由于匹配的对象和灰度有关系. The rare cases in which the very slow classical gray-valuebased matching is to be preferred com…

SSD:Single Shot MultiBox Detector Intro SSD是一套one-stage算法实现目标检测的框架,速度很快,在当时速度超过了yolo,精度也可以达到two-stage的精度,可以与faster rcnn媲美,这套算法里用到了与faster rcnn的anchor相似的概念-default box,也解决了多尺度问题对one-stage的影响-对不同大小的feature map进行滑窗分类,使得不同尺度的feature map的分类器对原图目标尺度更加敏感. o…

Direct Monocular Odometry Using Points and Lines Abstract 大多数VO都用点: 特征匹配 / 基于像素intensity的直接法关联. 我们做了一种直接法算法结合了点和edge. 它在纹理少的场景下工作的更好,而且对于光线的变化和快速的运动的情况下通过扩大收敛域(convergence basin - 盆)的方式提升鲁棒性. 我们对于关键帧保持了depth map. Tracking: 相机位姿是通过最小化广度误差和几何误差(匹配的edge…