摘要细粒度图像分类问题是计算机视觉领域一项极具挑战的研究课题, 其目标是对子类进行识别
, 如区分不同种类的鸟. 由于子类别间细微的类间差异和较大的类内差异, 传统的分类算法不得不 …

Bridge inspection and monitoring are usually used to evaluate the status and integrity of
bridge structures to ensure their safety and reliability. Computer vision (CV)-based methods …

This paper proposes a method to modify a traditional convolutional neural network (CNN)
into an interpretable CNN, in order to clarify knowledge representations in high conv-layers …

Pedestrian detection has progressed significantly in the last years. However, occluded
people are notoriously hard to detect, as their appearance varies substantially depending on …

This paper aims to quantitatively explain the rationales of each prediction that is made by a
pre-trained convolutional neural network (CNN). We propose to learn a decision tree, which …

Fine-grained classification is challenging because categories can only be discriminated by
subtle and local differences. Variances in the pose, scale or rotation usually make the …

Pooling second-order local feature statistics to form a high-dimensional bilinear feature has
been shown to achieve state-of-the-art performance on a variety of fine-grained …

We propose a simple and straightforward way of creating powerful image representations
via cross-dimensional weighting and aggregation of deep convolutional neural network …

Current approaches for fine-grained recognition do the following: First, recruit experts to
annotate a dataset of images, optionally also collecting more structured data in the form of …

Part models of object categories are essential for challenging recognition tasks, where
differences in categories are subtle and only reflected in appearances of small parts of the …