论文阅读《Self-Attention Guidance and Multiscale Feature Fusion-Based UAV Image Object Detection》 摘要 无人机(UAV)图像的目标检测是近年来研究的热点。现有的目标检测方法在一般场景上取得了很好的结果,但无人机图像存在固有的挑战。无人机图像的检测精度受到复杂背景、显著尺度差异和密集排列的小物体的限制。
In this paper we present a method for the detection of wrong feature correspondences in a local feature based object detection system. Common visual objects in different images share not only similar local features but also a similar spatial layout of their features. We will utilize this fact in...
在计算机视觉中,识别不同尺度的物体是一个基本的挑战。构建在图像金字塔之上的特征金字塔(简而言之,我们称这些特征金字塔为featurized image pyramid)构成了标准解决方案的基础,如下图所示(a)所示。这些金字塔是尺度不变的,因为一个物体的尺度变化是通过改变其在金字塔中的层级来抵消的。直观地说,这个属性使模型能够通过...
Without bells and whistles, our BBFE improves different baseline methods (both anchor-based and anchor-free) by a large margin ( [Math Processing Error] \\sim 2.0 points higher AP) on COCO, surpassing common feature pyramid networks including FPN and PANet.Ji, Haoqin...
Rich feature hierarchies for accurate object detection and semantic segmentation 一、摘要 在PASCAL VOC标准数据集上测量的目标检测性能在最近几年趋于稳定。性能最好的方法是复杂的集成系统,它通常将多个低层图像特性与高层上下文结合起来。在本文中,我们提出了一种简单、可扩展的检测算法,相对于之前VOC 2012的最佳...
In most of the object detection tasks, the low-level feature maps with high resolution contain more location and detail information. However, the low-level feature maps lack semantic information. The high-level feature maps have more semantic information based on the convolution operator. The local...
Normalizing Flow based Feature Synthesis for Outlier-Aware Object Detection harrylin 1 人赞同了该文章 出处:CVPR 2023 代码:未公开 想法:现有的方法VOS为对物体进行分类,构建一个基于条件高斯分布的objectness模型。VOS根据objectness模型采样生成一些outliers样本,用于生成决策边界。因此,构建objectness模型成为能区分未...
与其他强大的分类器(例如,Rotation-based SVM,结构化的SVM,旋转森林),增强型的迭代选择弱学习者从候选人弱分类器从上一轮努力处理的例子,它们一边被视为一个增强模型集成前成绩,贪婪地最小化一个指数损失函数。每一个弱学习者都能对样本进行重估,然后弱学习者会更关注那些被前一个学习者错误分类的例子。利用该...
本篇学习报告基于CVPR 2017的文章:《Feature Pyramid Networks for Object Detection》 一、概述 作者为目标检测任务提出了一种多尺度的特征融合算法:FPN(Feature Pyramid Networks),也就是近些年广泛运用的特征金字塔结构。原来多数的目标检测算法都只是采用顶层的特征图做预测。实际上我们只知道,低层的(low-level)特征...
Feature pyramid network is widely used in advanced object detection. By simply changing the network connection, the performance of small object detection can be greatly improved without increasing th...