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
active learningsemi-supervised learningObject detection is a challenging task that requires a large amount of labeled data to train high-performance models. However, labeling huge amounts of data is expensive, making it difficult to train a good detector with limited labeled data. Existing approaches...
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、... ...
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 实验上来看大部分比 random 强 2.Localization-Aware Active Learning for Object Detection 检测任务中的主动学习框架图 localization tightness:对于两阶段目标检测网络,模型会根据 region proposal 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 ...
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 ...
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 ...
https://github.com/baifanxxx/awesome-active-learning Note:前 1、2、3 节都是一些主动学习基础内容,也有很多文章做过类似的整理和介绍,如果你已经很了解了,可以直接跳到 4 节以后阅读。 介绍 主动学习是一种通过主动选择最有价值的样本进行标注的机器学习或人工智能方法。其目的是使用尽可能少的、高质量的样本...
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...
Object Detection Natural Language Processing (NLP) Sentence Classification Named Entity Recognition Domain adaptation/Transfer learning Metric learning/Pairwise comparison/Similarity learning One/Few/Zero-shot learning - Graph Processing etc. 由于篇幅限制,主动学习与 AI 结合的领域和工作可以参见以下...