Abstract: We tackle a new task of few-shot object counting and detection. Given a few exemplar bounding boxes of a target object class, we seek to count and detect all objects of the target class. This task shares the same supervision as the few-shot object counting but additionally outputs...
Few-Shot Object Counting and DetectionECCV 2022FSCD-147 & FSCD-LVISPDFCODE Mutually Reinforcing Structure with Proposal Contrastive Consistency for Few-Shot Object DetectionECCV 2022PASCAL VOC & MS COCOPDFCODE Few-Shot End-to-End Object Detection via Constantly Concentrated Encoding across HeadsECCV ...
In this paper, we tackle a challenging problem of Few-shot Object Detection rather than recognition. We propose Power Normalizing Second-order Detector consisting of the Encoding Network (EN), the Multi-scale Feature Fusion (MFF), Second-order Pooling (SOP) with Power Normalization (PN), the ...
Imbalanced learning(不平衡学习),这种机器学习方法从数据集中学习y的偏态分布(severely skewed distribution),例如fraud detection(欺诈检测)、catastrophe anticipation(灾难预测)。相比之下,FSL对y的训练和测试只是使用了几个样本。 Transfer learning(迁移学习),这种机器学习方法从有大量训练数据的源域和源任务学到的知识...
Frustratingly SimpleFew-ShotObject Detection 摘要从几个例子中检测稀有物体是一个新兴的问题。先前的研究表明元学习是一种很有前途的方法。但是,精细的调音技术没有引起足够的重视。我们发现,仅微调现有探测器的最后一层稀有类是至关重要的少数射击目标检测任务。这种简单的方法比元学习方法的性能要高出约2 ~ 20点...
(1) to reduce irrelevant information in the image, (2) to recover useful information and prevent information loss, (3) to make the information detectable and (4) to make the data simpler so that the reliability of recognition and detection is improved and thus the image can be better ...
Existing correlation-based few-shot counting approaches suffer from the coarseness and low semantic level of the correlation. ... Z You,K Yang,W Luo,... 被引量: 0发表: 2022年 Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection We study the challenging incremental few-...
counting method based on the regional image, there are some problems such as complicated illumination conditions, serious occlusion of object, and fast movement of sheep, which bring greater difficulty for target detection and lead to the lower detection accuracy and the insensitive detection ...
The specific object counting task is from Amazon Bin Image Dataset (ABID) Challenge, which is to predict the quantity of the object in a bin, given an image and the target category. When the maximal quantity of an object in a bin is set to a constant (here is 5), we formulate this...
Abstract: We tackle a new task of few-shot object counting and detection. Given a few exemplar bounding boxes of a target object class, we seek to count and detect all objects of the target class. This task shares the same supervision as the few-shot object counting but additionally outputs...