[2]Path Aggregation Network for Instance Segmentation [3]EfficientDet: Scalable and Efficient Object Detection [4]Focal Loss for Dense Object Detection [5]YOLOv4: Optimal Speed and Accuracy of Object Detection [6]Single Shot MultiBox Detector (SSD) [7...
* Bag of Freebies (BoF) for detector: CIoU-loss, CmBN, DropBlock regularization, Mosaic data augmentation, Self-Adversarial Training, Eliminate grid sensitivity, Using multiple anchors for a single ground truth, Cosine annealing scheduler [52], Optimal hyperparameters, Random training shapes * Bag ...
话不多说,现在就开始对YOLO V4进行总结。 YOLO V4的论文链接在这里,名为《YOLOv4: Optimal Speed and Accuracy of Object Detection》,相信大家也是经常看到这几个词眼:大神接棒、YOLO V4来了、Tricks 万花筒等等。 没错,通过阅读YOLO V4的原文,我觉得它更像一篇目标检测模型Tricks文献综述,可见作者在目标检测领域...
一般情况下,我们需要一个backbone结构,也即我们的骨干网络,预测分类和目标边框回归(在GPU上面燥的情况):常见的有VGG、ResNet、ResNeXt、DenseNet;检测目标在CPU上,常见的有SqueezeNet、MobileNet、ShufflfleNet。head部分一般分为两部分:one-stage object detectorandtwo-stage object detector。two-stage object detector的...
For those plugin modules and post-processing methods that only increase the inference cost by a small amount but can significantly improve the accuracy of object detection, we call them “bag of specials”. 主要作用是增强模型某一方面的属性,如增大感受野( receptive field),引入attention机制,增强特征整...
【论文笔记】YOLOv4: Optimal Speed and Accuracy of Object Detection, 摘要:有很多特征可以提高卷积神经网络(CNN)的准确性。需要在大型数据集上对这些特征的组合进行实际测试,并需要对结果进行理论证明来验证这些特征的有效性。某些特征仅在某些模型上运行,并且
我们验证了在检测器训练的过程中最先进的 Bag-of Freebies 和Bag-of-Specials methods of object detection的影响。 我们修改了最先进的方法使得它们在单个GPU上训练更有效和适合,例如CBN、PAN、SAM等等。 2.相关工作: 2.1 目标检测模型 现代检测器通常由两个部分组成,一个是在ImageNet上预训练的主干,另一个是用...
Table 2. Influence of BoF and Mish on the CSPResNeXt-50 classifier accuracy. Table 3. Influence of BoF and Mish on the CSPDarknet-53 classifier accuracy. 4.3.Influence of different features on Detector training(特征对探测器训练的影响)
Paper:《YOLOv4: Optimal Speed and Accuracy of Object Detection》的翻译与解读 YOLOv4的评价 1、四个改进和一个创新 这篇文章主要有四个改进+一个创新,但组合了大约20项近几年来各种深度学习和目标检测领域的tricks。可以说,这篇论文有创新和改进,但多数是微小的改进。然而这篇文章对比了大量的、近几年新出来...
YOLOv4: Optimal Speed and Accuracy of Object Detection 论文地址:https://arxiv.org/abs/2004.10934 代码地址:https://github.com/AlexeyAB/darknet Abstract There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy. Practical testing of combinations of ...