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 实验上来看大部分比...
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,...
论文:Multiple Instance Active Learning for Object Detection 该论文首次提出了多实例主动目标检测(MI-AOD)方法,并详细阐述了其实现原理和实验结果。 实验结果表明,MI-AOD在PASCAL VOC和MS COCO数据集上均取得了显著的性能提升。 代码:GitHub - yuantn/MI-AOD 该代码库提供了MI-AOD方法的实现代码,包括数据预处...
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...
【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...
Active Learning For Object Detection Computes informativeness of a single object detection using MC Dropout and DBSCAN. After computing the model’s uncertainty per detection, it aggregates the individual uncertainty values in two different ways. The first metric selects the images with crowded scenes...
Learning Loss for Active Learning https://arxiv.org/abs/1905.03677?context=cs.CV VAAL Variational Adversarial Active Learning https://arxiv.org/abs/1904.00370 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题中被广泛应用。
As our team was designing the active learning pipeline, we considered using various different options for the machine learning “backend” infrastructure where the object detection model would be (re)trained and where drafts of new tags would be created. The new Azure Custom Vision Service...
Learning Loss for Active Learning https://arxiv.org/abs/1905.03677?context=cs.CV VAAL Variational Adversarial Active Learning https://arxiv.org/abs/1904.00370 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题中被广泛应用。
Our work is also based on a student-teacher framework, but extends it with active learning strategies for selecting most informa- tive WA or UA data, which are fully annotated by humans. Active Learning for Object Detection (ALOD). The tra- ditional active learning st...