Jin. Active and semi-supervised learning for object detection with imperfect data. In Cognitive Systems Research, 2017. 3P. Rhee, E. Erdenee, S. Kyun, M. Ahmed, and S. Jin, "Active and semi-supervised learning
论文地址:Learning a Neural Solver for Multiple Object Tracking Learning a Neural Solver for Multiple Object Tracking 一、 摘要 二、 介绍 三、 图问题解释追踪 问题设置 网络流公式 从学习代价到预测方案 四、 消息传递追踪 MPN 消息传递网络 时间感知消息传递 特征嵌入 训练推导 五、... ...
Localization-Aware Active Learning for Object Detection (ACCV, 2018) 这篇文章是一篇比较经典的 Active Learning 应用于图像识别中Object Detection tasks。文章发在18年的 ACCV ,目前引量13,干货很多,想法很不错。 问题背景 在训练目标识识别任务时,需要大量的有标记数据,然而这些标记往往是昂贵或时间开销极大的,...
PyTorch implementation of our paper:Plug and Play Active Learning for Object Detection Requirements Our codebase is built on top ofMMDetection, which can be installed following the offcial instuctions. Usage Installation python setup.py install ...
Active learning for Object Detection 检测一般先对 instance (比如 anchor 输出)进行打分,通过 score aggregation 方法得到图片级别的分数,一般 aggregation 方式:max/avereage/sum 1.Active Learning for Deep Object Detection 通过对每个检测框的 margin sampling 进行 aggregation 来得到最终的结果 ...
TABLE V:Meanaverage precisionevaluated on: a) both manual and active learning test data. b) manual test data only. Manual and AL test dataManual test data only ManualActive LearningManualActive Learning bicycle+1.36+5.94+2.28+3.18 person+0.74+3.28+1.28+1.35 ...
The process of active object detection (active learning for object detection) is shown in the figure below. First, a small set of images (the labeled set) with instance labels and a large set of images (the unlabeled set) without labels are given. For each image, the label consists of ...
Active Learning for Deep Object DetectionClemens-Alexander Brust 1 , Christoph Käding 1,2 and Joachim Denzler 1,21 Computer Vision Group, Friedrich Schiller University Jena, Germany2 Michael Stifel Center Jena, Germany{f author, s author}@uni-jena.deKeywords: Active Learning, Deep Learning, ...
Therefore, document object detection (DOD) has been studied as a preprocessing step for optical character recognition. Given the ease of acquiring image data, reducing annotation time and effort through transfer learning and active learning has emerged as a key research challenge. In this study, a...
【Learning Loss for Active Learning】—https://arxiv.org/abs/1905.03677%3Fcontext%3Dcs.CV VAAL 【Variational Adversarial Active Learning】—https://arxiv.org/abs/1904.00370 5. 应用场景 由于主动学习解决的是如何从无标签数据中选择价值高的样本进行标注,所以在数据标签难以获得、标注成本大的场景和实际问...