Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object predictions using a neural network. One of the methods includes receiving respective project
一、 摘要 refinement module 包含2个模块(anchor refinement module 和 object detection module) anchor refinement module --- 去掉负样本的anchor, 缩小分类器的搜索空间 object detection module --- 粗略的调整anchors 的位置和大小,为后面的回归提供更优质的anchors 同时设计一个transfer connection block, 将 anc...
在我么看来,目前最先进的两阶段方法,比如Faster R-CNN,R-FCN和FPN,相对于单阶段方法有三个优势 (1)采用带抽样启发的两阶段结构处理类不平衡问题;(2)采用两步级联对目标盒参数进行回归;(3)使用两个阶段的特征来描述目标。在工作中,我们 设计一 种新的目标检测框架, 叫 RefineDet继承了这两种方法的优点,并克服...
As we know, image classification is probably the most common use for deep neural network in computer vision. Most of the CNN networks are designed to extract features from images which can be later used to recognize it. This lead to an intuitive strategy for object detection: the region based...
Single-Shot Refinement Neural Network for Object Detection 论文链接:arxiv.org/pdf/1711.0689代码链接:github.com/sfzhang15/Re今天接着看CVPR 2018的文章,不过总的来说,这篇文章亮点不是很多,谈不上insight,大致上可以看做将Faster RCNN的two stages检测方法和SSD结合了起来,在保证performance的情况下,取得了...
对于object detection来说,two-stage方法(如 Faster RCNN)取得了最高的accuracy, one-stage方法(如 SSD)的优势是效率高。为了继承两类优势并克服缺点,这篇论文提出了新颖的single-shot的detector,叫做 Refin…
Bag of Freebies for Training Object Detection Neural Networks,李沐大神19年2月的新作,用卷积神经网络进行目标检测的一些技巧。 论文:Bag of Freebies for Training Object Detection Neural Networks 本文主要讨论训练目标检测网络过程中的一些tricks,在不改变模型结构、不改变损失函数、不牺牲推断时间...
Figure 1: Example DetectNet output for vehicle detection. In order to get you up and running as fast as possible with this new workflow, DIGITS now includes a new exampleneural networkmodel architecture called DetectNet. Figure 1 shows an example of the output of DetectNet when trained to detec...
MSCNN论文解读-A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection,程序员大本营,技术文章内容聚合第一站。
Popular deep learning–based approaches using convolutional neural networks (CNNs), such as YOLO, SSD, or R-CNN, automatically learn to detect objects within images.You can choose from two key approaches to get started with object detection using deep learning: Use pretrained object detectors...