选择性搜索是一种成熟且非常有效的无监督object proposal生成算法,它使用颜色相似性、纹理相似性等因素来生成object proposal。然而,object proposal的数量很大,排名也不准确。为了避免这个问题,作者使用选择性搜索算法中的对象排序来删除不精确的object proposal。 具体而言,作者选择排名列表中与基类的ground truth对象不重叠...
Juan-Manuel Perez-Rua, Xiatian Zhu, Timothy M. Hospedales, Tao Xiang; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13846-13855 文章链接:Incremental Few-Shot Object Detection 代码:未开源 1.本文创新点: 现有小样本检测方法旨在解决检测模型依赖...
本文分享论文『Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning』,由新国立&哈工大提出 Incremental-DETR 进行基于自监督学习的增量 Few-Shot 目标检测,性能SOTA! 详细信息如下: 论文链接:https://arxi...
具体而言,作者选择排名列表中与基类的ground truth对象不重叠的前O个对象作为伪ground truth object proposal。作者将伪ground truth object proposal表示为b′。 为了对这些选定object proposal进行预测,作者按照DETR的预测头那样,为所有选定object proposal引入一个新的类标签c′,作为伪ground truth标签以及基类标签。 In...
【论文阅读笔记】EfficientDet:Scalable and Efficient Object Detection 论文地址:EfficientDet 论文总结 本文是基于EfficientNet展开的检测网络,其提出了一种新的特征融合手段(BiFPN),以及检测器上的缩放方案(如EfficientNet一样的多维度组合缩放方案),可以得到一个高效率又高性能的网络。 BiFPN通过对FPN...
Few-shot Object Detection via Feature Reweighting 模型组成 Feature Extractor Reweighting Module Prediction Layer 训练策略 摘要:这是ICCV2019的一片文章,主要是将Few-Shot Learning用于物体检测上面。其核心思是使用具有大量标签的base类训练一个特征调整模块,通过这个模块 incremental few-shot learning论文阅读 对每...
Transfer learningIncremental few-shot object detectionAs a challenging problem in machine learning, incremental few-shot object detection (iFSD) [1] aims to incrementally detect novel classes with few examples, while keeping the previous knowledge without revisiting base classes. Here, we propose two ...
<p id="abspara0010" view="all"> Traditional object detectors based on deep learning rely on plenty of labeled samples, which are expensive to obtain. Few-shot object detection (FSOD) attempts to solve this problem, learning detection objects from a few l
We aim to obtain a few-shot detection model that can learn to detect novel object when there ...
Incremental few-shot object detection aims at detecting novel classes without forgetting knowledge of the base classes with only a few labeled training data from the novel classes. Most related prior works are on incremental object detec... N Dong,Y Zhang,M Ding,... - 《Arxiv》 被引量: 0...