最近几年cascaded detection用的也很多,特别是一些“small objects in large scenes”的任务,像face detection,pedestrian detection等。 3.4 Network Pruning and Quantifification 3.4.1 Network Pruning 近年来的网络剪枝方法通常经过迭代训练和剪枝过程,即剪枝过程。,即在每一阶段训练后只去除一小部分不重要的权重,并...
Perform classification, object detection, transfer learning using convolutional neural networks (CNNs, or ConvNets), create customized detectors Object detection is a computer vision technique for locating instances of objects in images or videos. Object detection algorithms typically leveragemachine learning...
现代的深度学习目标检测器也同样使用了 cascaded detection 的方法,尤其是当要检测 small objects in large scenes 时(如人脸检测、行人检测),这种方法更是发挥了至关重要的作用。 3.4 网络剪枝和量化 3.4.1 网络剪枝 3.4.2 网络量化 3.4.3 网络蒸馏 3.5 轻量级网络设计 3.5.1 Factorizing Convolutions 分离卷积:...
The importance of object detection within computer vision, especially in the context of detecting small objects, has notably increased. This thorough survey extensively examines small object detection across various applications, consolidating and outlining the available methodologies. Traditional papers on sma...
论文链接:Bottom-up Object Detection by Grouping Extreme and Center Points Motivation:使用矩形的bounding box表示object的位置,这种方式仔细想想就会觉得有点违和,因为bounding box里会有很多的背景。作者希望构建一个detector可以之间预测object的4个extreme points (top-most, left-most, bottom-most, right-most)以...
Small object detection is one of the most challenging problems in computer vision. Algorithms based on state-of-the-art object detection methods such as R-CNN, SSD, FPN, and YOLO fail to detect objects of very small sizes. In this study, we propose a novel method to detect very small ob...
Object detection has been widely applied in various fields with the rapid development of deep learning in recent years. However, detecting small objects is still a challenging task because of the limited information in features and the complex background. To further enhance the detection accuracy of...
三. Identifying issues with detecting small objects 这一节,我们首先概述下 MS COCO 数据和实验中用到的目标检测方法。然后我们讨论 MS COCO 数据集和使用 anchor 类方法的问题,它们都是增加小目标检测难度的原因。 1. MS COCO 我们使用 MS COCO 检测数据集进行了实验,MS COCO 2017 检测数据集包含 118287 张...
Object detection is a fundamental and important problem in computer vision. Although impressive results have been achieved on large/medium sized objects in large-scale detection benchmarks (e.g. the COCO dataset), the performance on small objects is far
A closer look: Small object detection in Faster R-CNN Improving Small Object Proposals for Company Logo Detection 这里主要分析 Faster R-CNN 对小目标检测的性能分析及改进。 主要是 多尺度 RPN 和多尺度分类网络 数据中目标尺寸分布 3.1 Region Proposals of small objects ...